Conveying value of implementing an integrated data management and protection system

ABSTRACT

A system and method are described for conveying to a user the value it would receive by implementing an integrated system to protect and manage its data. An integrated system can combine archiving, backup, snapshot management, reporting, secure data access, eDiscovery and data analytics, among other functions, thus simplifying data protection and data management for an organization. The system generates a value dashboard, exhibiting value data, including data and graphics portraying the benefits to a user of implementing an integrated data management and protection system. Value may be evaluated with reference to simplification and efficiency, risk reduction, and unlocking data value.

INCORPORATION BY REFERENCE TO ANY PRIORITY APPLICATIONS

This application claims the benefit of U.S. Provisional Patent Application No. 62/010,676 filed Jun. 11, 2014, entitled “CONVEYING VALUE OF IMPLEMENTING AN INTEGRATED DATA MANAGEMENT AND PROTECTION SYSTEM” which is incorporated herein by reference in its entirety. Any and all applications, if any, for which a foreign or domestic priority claim is identified in the Application Data Sheet of the present application are hereby incorporated by reference under 37 CFR 1.57.

BACKGROUND

Businesses worldwide recognize the commercial value of their data and seek reliable, cost-effective ways to protect the information stored on their computer networks while minimizing impact on productivity. Protecting information is often part of a routine process that is performed within an organization. A company might back up critical computing systems such as databases, file servers, web servers, and so on as part of a daily, weekly, or monthly maintenance schedule. The company may similarly protect computing systems used by each of its employees, such as those used by an accounting department, marketing department, engineering department, and so forth.

Given the rapidly expanding volume of data under management, companies also continue to seek innovative techniques for managing data growth, in addition to protecting data. For instance, companies often implement migration techniques for moving data to lower cost storage over time and data reduction techniques for reducing redundant data, pruning lower priority data, etc. Enterprises also increasingly view their stored data as a valuable asset. Along these lines, customers or users are looking for solutions that not only protect and manage, but also leverage their data. For instance, solutions providing data analysis capabilities, information management, improved data presentation and access features, and the like, are in increasing demand.

For managing its data, a business typically relies on data storage software and/or services provided by third parties. These providers offer an array of data management systems that address the varying storage needs of their users. While users generally appreciate having multiple services to choose from, they often find it difficult to identify which systems best meet their data management needs. Likewise, providers struggle to determine which services to market toward a potential user because each user's needs vary depending on its industry and particular circumstances.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a block diagram illustrating an exemplary information management system.

FIG. 1B is a detailed view of a primary storage device, a secondary storage device, and some examples of primary data and secondary copy data.

FIG. 1C is a block diagram of an exemplary information management system including a storage manager, one or more data agents, and one or more media agents.

FIG. 1D is a block diagram illustrating a scalable information management system.

FIG. 1E illustrates certain secondary copy operations according to an exemplary storage policy.

FIGS. 1F-1H are block diagrams illustrating suitable data structures that may be employed by the information management system.

FIG. 2 is a block diagram illustrating some salient portions of a system for identifying value associated with an integrated data management and protection system for a customer or user, according to an illustrative embodiment of the present invention.

FIG. 3 depicts some salient operations of a method for identifying value associated with an integrated data management and protection system for a user.

FIGS. 4A-J depicts an illustrative graphical user interface showing data entry fields for receiving information related to data management and protection for a user in the illustrative system.

FIGS. 5A and 5B depict an illustrative graphical user interface showing a value dashboard for conveying value of a user implementing a data management and protection system.

FIGS. 6A and 6B depict an illustrative graphical user interface showing a value story for conveying value of a user implementing a data management and protection system and receiving information related to data management and protection needs of the user.

FIG. 7 depicts an illustrative graphical user interface or display for conveying value of a user implementing a data management and protection system such as for cloud management.

FIG. 8A through 8E depict suitable graphical user interfaces or displays showing input boxes or sliders for receiving data on various variables related to virtual machine archiving, virtualization costs, loaded recovery costs, recovery capabilities, and legal discovery savings, respectively, and showing bar charts for depicting comparisons between existing products/performance and corresponding products/performance when implemented using another supplier.

FIG. 9A through 9E depict suitable graphical user interfaces or displays showing alternatives for receiving data at various variables and providing computed information.

FIG. 10 is a curve associated with a risk score between 0.0 and 10.0 using a semi-complex straight line curve with three different slopes and four points that define the curve.

DETAILED DESCRIPTION

Systems and methods are disclosed for conveying to a customer or user the value received by implementing an integrated solution or system to protect and manage data. The system generates a value dashboard, exhibiting value data, including data and graphics portraying the benefits to a user of an integrated data management and protection system and changes from an existing system that the user may have.

The system computes and conveys value in statistics and graphs showing improvements the user would receive by implementing, e.g. an integrated data storage and management system or solution. The system can display this value data in relation to alternative data management and protection systems, such as systems offered by different data management and protection providers. Furthermore, the system can calculate scores representing value received by a user. One score generated by the system is a data and information risk exposure score. The data and information risk exposure score, or DIRE Index, reflects an aggregation of operational complexity, recovery efficiency, and relative exposure to legal issues, compliance failures, downtime or data loss. Further, the system can generate scripts, examples, or vignettes that to help convey the information computed by the system.

Overall, the system described herein provides 1) a definition of value for a user, 2) a computer-implemented mapping of user data to the value definition, and 3) calculators and processes that employ the user data in certain tools to generate output useful in depicting and explaining the calculated value. Regarding the definition of value, data storage companies address cost reduction, risks and getting value from data. The present system formalizes process and actually quantifies value based a new definition of it, where the system provides weightings to at least three value components—Simplification, Risk Reduction and Unlocking Data Value (e.g. an equal weighting to each), as well as provide clear definitions of value under each value component, as discussed below.

Regarding user data: the system leverages two types of data: 1) customer data previously a) gathered by the company via survey, b) statistically validated (e.g. by third party consultant), and c) mapped into the three components of the Value Definition; and 2) data supplied by the current user of the system. Prior customer data provides baseline values for different areas of impact and different metrics of value, providing a credible foundation when presenting value calculations back to users. Users can change these values freely, but prior customer data provides the credible baseline—empirical data to provide more accurate, automatic data calculations.

Regarding automatically mapping user data into the value definition, the system a) gathers user data by obtaining or surveying user data, b) statistically validates the user data, and c) maps it into the three value components. Regarding the use of the value definition and tools, the system combines the new definition of value with the user data to provide a foundation or credibility when presenting value calculations back to users or users. These components in combination (definition, data and tools), make a complete package.

Examples of such systems and methods are described in further detail herein, in reference to FIGS. 2-5. The system components and functionality may be configured and/or incorporated into information management systems such as those described herein in FIGS. 1A-1H.

Information Management System Overview

With the increasing importance of protecting and leveraging data, organizations simply cannot afford to take the risk of losing critical data. Moreover, runaway data growth and other modern realities make protecting and managing data an increasingly difficult task. There is therefore a need for efficient, powerful, and user-friendly systems for protecting and managing data.

Depending on the size of the organization, there are typically many data production sources which are under the purview of tens, hundreds, or even thousands of employees or other individuals. In the past, individual employees were sometimes responsible for managing and protecting their data. A patchwork of hardware and software point systems has been applied in other cases. These systems were often provided by different vendors and had limited or no interoperability.

Certain embodiments described herein provide systems and methods capable of addressing these and other shortcomings of prior approaches by implementing unified, organization-wide information management. FIG. 1A shows one such information management system 100, which generally includes combinations of hardware and software configured to protect and manage data and metadata, which is generated and used by the various computing devices in information management system 100. The organization that employs the information management system 100 may be a corporation or other business entity, non-profit organization, educational institution, household, governmental agency, or the like.

Generally, the systems and associated components described herein may be compatible with and/or provide some or all of the functionality of the systems and corresponding components described in one or more of the following U.S. patents and patent application publications assigned to CommVault Systems, Inc., each of which is hereby incorporated in its entirety by reference herein:

-   -   U.S. Pat. No. 7,035,880, entitled “Modular Backup and Retrieval         System Used in Conjunction With a Storage Area Network”;     -   U.S. Pat. No. 7,107,298, entitled “System And Method For         Archiving Objects In An Information Store”;     -   U.S. Pat. No. 7,246,207, entitled “System and Method for         Dynamically Performing Storage Operations in a Computer         Network”;     -   U.S. Pat. No. 7,315,923, entitled “System And Method For         Combining Data Streams In Pipelined Storage Operations In A         Storage Network”;     -   U.S. Pat. No. 7,343,453, entitled “Hierarchical Systems and         Methods for Providing a Unified View of Storage Information”;     -   U.S. Pat. No. 7,395,282, entitled “Hierarchical Backup and         Retrieval System”;     -   U.S. Pat. No. 7,529,782, entitled “System and Methods for         Performing a Snapshot and for Restoring Data”;     -   U.S. Pat. No. 7,617,262, entitled “System and Methods for         Monitoring Application Data in a Data Replication System”;     -   U.S. Pat. No. 7,747,579, entitled “Metabase for Facilitating         Data Classification”;     -   U.S. Pat. No. 8,156,086, entitled “Systems And Methods For         Stored Data Verification”;     -   U.S. Pat. No. 8,170,995, entitled “Method and System for Offline         Indexing of Content and Classifying Stored Data”;     -   U.S. Pat. No. 8,229,954, entitled “Managing Copies Of Data”;     -   U.S. Pat. No. 8,230,195, entitled “System And Method For         Performing Auxiliary Storage Operations”;     -   U.S. Pat. No. 8,285,681, entitled “Data Object Store and Server         for a Cloud Storage Environment, Including Data Deduplication         and Data Management Across Multiple Cloud Storage Sites”;     -   U.S. Pat. No. 8,307,177, entitled “Systems And Methods For         Management Of Virtualization Data”;     -   U.S. Pat. No. 8,364,652, entitled “Content-Aligned, Block-Based         Deduplication”;     -   U.S. Pat. No. 8,578,120, entitled “Block-Level Single         Instancing”;     -   U.S. Pat. Pub. No. 2006/0224846, entitled “System and Method to         Support Single Instance Storage Operations”;     -   U.S. Pat. Pub. No. 2009/0319534, entitled “Application-Aware and         Remote Single Instance Data Management”;     -   U.S. Pat. Pub. No. 2012/0150818, entitled “Client-Side         Repository in a Networked Deduplicated Storage System”; and     -   U.S. Pat. Pub. No. 2012/0150826, entitled “Distributed         Deduplicated Storage System”.

The information management system 100 can include a variety of different computing devices. For instance, as will be described in greater detail herein, the information management system 100 can include one or more client computing devices 102 and secondary storage computing devices 106.

Computing devices can include, without limitation, one or more: workstations, personal computers, desktop computers, or other types of generally fixed computing systems such as mainframe computers and minicomputers. Other computing devices can include mobile or portable computing devices, such as one or more laptops, tablet computers, personal data assistants, mobile phones (such as smartphones), and other mobile or portable computing devices such as embedded computers, set top boxes, vehicle-mounted devices, wearable computers, etc. Computing devices can include servers, such as mail servers, file servers, database servers, and web servers.

In some cases, a computing device includes virtualized and/or cloud computing resources. For instance, one or more virtual machines may be provided to the organization by a third-party cloud service vendor. Or, in some embodiments, computing devices can include one or more virtual machine(s) running on a physical host computing device (or “host machine”) operated by the organization. As one example, the organization may use one virtual machine as a database server and another virtual machine as a mail server, both virtual machines operating on the same host machine.

A virtual machine includes an operating system and associated virtual resources, and is hosted simultaneously with another operating system on a physical host computer (or host machine). A hypervisor (typically software, and also known in the art as a virtual machine monitor or a virtual machine manager or “VMM”) sits between the virtual machine and the hardware of the physical host machine. One example of hypervisor as virtualization software is ESX® Server, by VMware, Inc. of Palo Alto, Calif.; other examples include MICROSOFT VIRTUAL SERVER® and MICROSOFT WINDOWS SERVER HYPER-V®, both by Microsoft Corporation of Redmond, Wash., and Sun XVM® by Oracle America Inc. of Santa Clara, Calif. In some embodiments, the hypervisor may be firmware or hardware or a combination of software and/or firmware and/or hardware.

The hypervisor provides to each virtual operating system virtual resources, such as a virtual processor, virtual memory, a virtual network device, and a virtual disk. Each virtual machine has one or more virtual disks. The hypervisor typically stores the data of virtual disks in files on the file system of the physical host machine, called virtual machine disk files (in the case of VMware virtual servers) or virtual hard disk image files (in the case of MICROSOFT VIRTUAL SERVER®). For example, VMware's ESX® Server provides the Virtual Machine File System (VMFS) for the storage of virtual machine disk files. A virtual machine reads data from and writes data to its virtual disk much the same way that an actual physical machine reads data from and writes data to an actual disk.

Examples of techniques for implementing information management techniques in a cloud computing environment are described in U.S. Pat. No. 8,285,681, which is incorporated by reference herein. Examples of techniques for implementing information management techniques in a virtualized computing environment are described in U.S. Pat. No. 8,307,177, also incorporated by reference herein.

The information management system 100 can also include a variety of storage devices, including primary storage devices 104 and secondary storage devices 108, for example. Storage devices can generally be of any suitable type including, without limitation, disk drives, hard-disk arrays, semiconductor memory (e.g., solid state storage devices), network attached storage (NAS) devices, tape libraries or other magnetic, non-tape storage devices, optical media storage devices, DNA/RNA-based memory technology, combinations of the same, and the like. In some embodiments, storage devices can form part of a distributed file system. In some cases, storage devices are provided in a cloud (e.g., a private cloud or one operated by a third-party vendor). A storage device in some cases comprises a disk array or portion thereof.

The illustrated information management system 100 includes one or more client computing device 102 having at least one application 110 executing thereon, and one or more primary storage devices 104 storing primary data 112. The client computing device(s) 102 and the primary storage devices 104 may generally be referred to in some cases as a primary storage subsystem 117. A computing device in an information management system 100 that has a data agent 142 installed and operating on it is generally referred to as a client computing device 102 (or, in the context of a component of the information management system 100 simply as a “client”). Depending on the context, the term “information management system” can refer to generally all of the illustrated hardware and software components. Or, in other instances, the term may refer to only a subset of the illustrated components. Similar terms for the same system are used interchangeably herein.

For instance, in some cases, the information management system 100 generally refers to a combination of specialized components used to protect, move, manage, manipulate, analyze, and/or process data and metadata generated by the client computing devices 102. However, the information management system 100 in some cases does not include the underlying components that generate and/or store the primary data 112, such as the client computing devices 102 themselves, the applications 110 and operating system operating on the client computing devices 102, and the primary storage devices 104. As an example, “information management system” may sometimes refer to one or more of the following components and corresponding data structures: storage managers, data agents, and media agents. These components will be described in further detail below.

Client Computing Devices

There are typically a variety of sources in an organization that produce data to be protected and managed. As just one illustrative example, in a corporate environment such data sources can be employee workstations and company servers such as a mail server, a web server, a database server, a transaction server, or the like. In the information management system 100, the data generation sources include the one or more client computing devices 102.

The client computing devices 102 may include any of the types of computing devices described above, without limitation, and in some cases the client computing devices 102 are associated with one or more users and/or corresponding user accounts, of employees or other individuals.

The information management system 100 generally addresses and handles the data management and protection needs for the data generated by the client computing devices 102. However, the use of this term does not imply that the client computing devices 102 cannot be “servers” in other respects. For instance, a particular client computing device 102 may act as a server with respect to other devices, such as other client computing devices 102. As just a few examples, the client computing devices 102 can include mail servers, file servers, database servers, and web servers.

Each client computing device 102 may have one or more applications 110 (e.g., software applications) executing thereon which generate and manipulate the data that is to be protected from loss and managed. The applications 110 generally facilitate the operations of an organization (or multiple affiliated organizations), and can include, without limitation, mail server applications (e.g., Microsoft Exchange Server), file server applications, mail client applications (e.g., Microsoft Exchange Client), database applications (e.g., SQL, Oracle, SAP, Lotus Notes Database), word processing applications (e.g., Microsoft Word), spreadsheet applications, financial applications, presentation applications, graphics and/or video applications, browser applications, mobile applications, entertainment applications, and so on.

The client computing devices 102 can have at least one operating system (e.g., Microsoft Windows, Mac OS X, iOS, IBM z/OS, Linux, other Unix-based operating systems, etc.) installed thereon, which may support or host one or more file systems and other applications 110.

The client computing devices 102 and other components in information management system 100 can be connected to one another via one or more communication pathways 114. For example, a first communication pathway 114 may connect (or communicatively couple) client computing device 102 and secondary storage computing device 106; a second communication pathway 114 may connect storage manager 140 and client computing device 102; and a third communication pathway 114 may connect storage manager 140 and secondary storage computing device 106, etc. (see, e.g., FIG. 1A and FIG. 1C). The communication pathways 114 can include one or more networks or other connection types including one or more of the following, without limitation: the Internet, a wide area network (WAN), a local area network (LAN), a Storage Area Network (SAN), a Fibre Channel connection, a Small Computer System Interface (SCSI) connection, a virtual private network (VPN), a token ring or TCP/IP based network, an intranet network, a point-to-point link, a cellular network, a wireless data transmission system, a two-way cable system, an interactive kiosk network, a satellite network, a broadband network, a baseband network, a neural network, a mesh network, an ad hoc network, other appropriate wired, wireless, or partially wired/wireless computer or telecommunications networks, combinations of the same or the like. The communication pathways 114 in some cases may also include application programming interfaces (APIs) including, e.g., cloud service provider APIs, virtual machine management APIs, and hosted service provider APIs. The underlying infrastructure of communication paths 114 may be wired and/or wireless, analog and/or digital, or any combination thereof; and the facilities used may be private, public, third-party provided, or any combination thereof, without limitation.

Primary Data and Exemplary Primary Storage Devices

Primary data 112 according to some embodiments is production data or other “live” data generated by the operating system and/or applications 110 operating on a client computing device 102. The primary data 112 is generally stored on the primary storage device(s) 104 and is organized via a file system supported by the client computing device 102. For instance, the client computing device(s) 102 and corresponding applications 110 may create, access, modify, write, delete, and otherwise use primary data 112. In some cases, some or all of the primary data 112 can be stored in cloud storage resources (e.g., primary storage device 104 may be a cloud-based resource).

Primary data 112 is generally in the native format of the source application 110. According to certain aspects, primary data 112 is an initial or first (e.g., created before any other copies or before at least one other copy) stored copy of data generated by the source application 110. Primary data 112 in some cases is created substantially directly from data generated by the corresponding source applications 110.

The primary storage devices 104 storing the primary data 112 may be relatively fast and/or expensive technology (e.g., a disk drive, a hard-disk array, solid state memory, etc.). In addition, primary data 112 may be highly changeable and/or may be intended for relatively short term retention (e.g., hours, days, or weeks).

According to some embodiments, the client computing device 102 can access primary data 112 from the primary storage device 104 by making conventional file system calls via the operating system. Primary data 112 may include structured data (e.g., database files), unstructured data (e.g., documents), and/or semi-structured data. Some specific examples are described below with respect to FIG. 1B.

It can be useful in performing certain tasks to organize the primary data 112 into units of different granularities. In general, primary data 112 can include files, directories, file system volumes, data blocks, extents, or any other hierarchies or organizations of data objects. As used herein, a “data object” can refer to both (1) any file that is currently addressable by a file system or that was previously addressable by the file system (e.g., an archive file) and (2) a subset of such a file (e.g., a data block).

As will be described in further detail, it can also be useful in performing certain functions of the information management system 100 to access and modify metadata within the primary data 112. Metadata generally includes information about data objects or characteristics associated with the data objects. For simplicity herein, it is to be understood that, unless expressly stated otherwise, any reference to primary data 112 generally also includes its associated metadata, but references to the metadata do not include the primary data.

Metadata can include, without limitation, one or more of the following: the data owner (e.g., the client or user that generates the data), the last modified time (e.g., the time of the most recent modification of the data object), a data object name (e.g., a file name), a data object size (e.g., a number of bytes of data), information about the content (e.g., an indication as to the existence of a particular search term), user-supplied tags, to/from information for email (e.g., an email sender, recipient, etc.), creation date, file type (e.g., format or application type), last accessed time, application type (e.g., type of application that generated the data object), location/network (e.g., a current, past or future location of the data object and network pathways to/from the data object), geographic location (e.g., GPS coordinates), frequency of change (e.g., a period in which the data object is modified), business unit (e.g., a group or department that generates, manages or is otherwise associated with the data object), aging information (e.g., a schedule, such as a time period, in which the data object is migrated to secondary or long term storage), boot sectors, partition layouts, file location within a file folder directory structure, user permissions, owners, groups, access control lists [ACLs]), system metadata (e.g., registry information), combinations of the same or other similar information related to the data object.

In addition to metadata generated by or related to file systems and operating systems, some of the applications 110 and/or other components of the information management system 100 maintain indices of metadata for data objects, e.g., metadata associated with individual email messages. Thus, each data object may be associated with corresponding metadata. The use of metadata to perform classification and other functions is described in greater detail below.

Each of the client computing devices 102 are generally associated with and/or in communication with one or more of the primary storage devices 104 storing corresponding primary data 112. A client computing device 102 may be considered to be “associated with” or “in communication with” a primary storage device 104 if it is capable of one or more of: routing and/or storing data (e.g., primary data 112) to the particular primary storage device 104, coordinating the routing and/or storing of data to the particular primary storage device 104, retrieving data from the particular primary storage device 104, coordinating the retrieval of data from the particular primary storage device 104, and modifying and/or deleting data retrieved from the particular primary storage device 104.

The primary storage devices 104 can include any of the different types of storage devices described above, or some other kind of suitable storage device. The primary storage devices 104 may have relatively fast I/O times and/or are relatively expensive in comparison to the secondary storage devices 108. For example, the information management system 100 may generally regularly access data and metadata stored on primary storage devices 104, whereas data and metadata stored on the secondary storage devices 108 is accessed relatively less frequently.

Primary storage device 104 may be dedicated or shared. In some cases, each primary storage device 104 is dedicated to an associated client computing device 102. For instance, a primary storage device 104 in one embodiment is a local disk drive of a corresponding client computing device 102. In other cases, one or more primary storage devices 104 can be shared by multiple client computing devices 102, e.g., via a network such as in a cloud storage implementation. As one example, a primary storage device 104 can be a disk array shared by a group of client computing devices 102, such as one of the following types of disk arrays: EMC Clariion, EMC Symmetrix, EMC Celerra, Dell EqualLogic, IBM XIV, NetApp FAS, HP EVA, and HP 3PAR.

The information management system 100 may also include hosted services (not shown), which may be hosted in some cases by an entity other than the organization that employs the other components of the information management system 100. For instance, the hosted services may be provided by various online service providers to the organization. Such service providers can provide services including social networking services, hosted email services, or hosted productivity applications or other hosted applications). Hosted services may include software-as-a-service (SaaS), platform-as-a-service (PaaS), application service providers (ASPs), cloud services, or other mechanisms for delivering functionality via a network. As it provides services to users, each hosted service may generate additional data and metadata under management of the information management system 100, e.g., as primary data 112. In some cases, the hosted services may be accessed using one of the applications 110. As an example, a hosted mail service may be accessed via browser running on a client computing device 102. The hosted services may be implemented in a variety of computing environments. In some cases, they are implemented in an environment having a similar arrangement to the information management system 100, where various physical and logical components are distributed over a network.

Secondary Copies and Exemplary Secondary Storage Devices

The primary data 112 stored on the primary storage devices 104 may be compromised in some cases, such as when an employee deliberately or accidentally deletes or overwrites primary data 112 during their normal course of work. Or the primary storage devices 104 can be damaged, lost, or otherwise corrupted. For recovery and/or regulatory compliance purposes, it is therefore useful to generate copies of the primary data 112. Accordingly, the information management system 100 includes one or more secondary storage computing devices 106 and one or more secondary storage devices 108 configured to create and store one or more secondary copies 116 of the primary data 112 and associated metadata. The secondary storage computing devices 106 and the secondary storage devices 108 may sometimes be referred to as a secondary storage subsystem 118.

Creation of secondary copies 116 can help in search and analysis efforts and meet other information management goals, such as: restoring data and/or metadata if an original version (e.g., of primary data 112) is lost (e.g., by deletion, corruption, or disaster); allowing point-in-time recovery; complying with regulatory data retention and electronic discovery (e-discovery) requirements; reducing utilized storage capacity; facilitating organization and search of data; improving user access to data files across multiple computing devices and/or hosted services; and implementing data retention policies.

The client computing devices 102 access or receive primary data 112 and communicate the data, e.g., over one or more communication pathways 114, for storage in the secondary storage device(s) 108.

A secondary copy 116 can comprise a separate stored copy of application data that is derived from one or more earlier-created, stored copies (e.g., derived from primary data 112 or another secondary copy 116). Secondary copies 116 can include point-in-time data, and may be intended for relatively long-term retention (e.g., weeks, months or years), before some or all of the data is moved to other storage or is discarded.

In some cases, a secondary copy 116 is a copy of application data created and stored subsequent to at least one other stored instance (e.g., subsequent to corresponding primary data 112 or to another secondary copy 116), in a different storage device than at least one previous stored copy, and/or remotely from at least one previous stored copy. In some other cases, secondary copies can be stored in the same storage device as primary data 112 and/or other previously stored copies. For example, in one embodiment a disk array capable of performing hardware snapshots stores primary data 112 and creates and stores hardware snapshots of the primary data 112 as secondary copies 116. Secondary copies 116 may be stored in relatively slow and/or low cost storage (e.g., magnetic tape). A secondary copy 116 may be stored in a backup or archive format, or in some other format different than the native source application format or other primary data format.

In some cases, secondary copies 116 are indexed so users can browse and restore at another point in time. After creation of a secondary copy 116 representative of certain primary data 112, a pointer or other location indicia (e.g., a stub) may be placed in primary data 112, or be otherwise associated with primary data 112 to indicate the current location on the secondary storage device(s) 108 of secondary copy 116.

Since an instance of a data object or metadata in primary data 112 may change over time as it is modified by an application 110 (or hosted service or the operating system), the information management system 100 may create and manage multiple secondary copies 116 of a particular data object or metadata, each representing the state of the data object in primary data 112 at a particular point in time. Moreover, since an instance of a data object in primary data 112 may eventually be deleted from the primary storage device 104 and the file system, the information management system 100 may continue to manage point-in-time representations of that data object, even though the instance in primary data 112 no longer exists.

For virtualized computing devices the operating system and other applications 110 of the client computing device(s) 102 may execute within or under the management of virtualization software (e.g., a VMM), and the primary storage device(s) 104 may comprise a virtual disk created on a physical storage device. The information management system 100 may create secondary copies 116 of the files or other data objects in a virtual disk file and/or secondary copies 116 of the entire virtual disk file itself (e.g., of an entire .vmdk file).

Secondary copies 116 may be distinguished from corresponding primary data 112 in a variety of ways, some of which will now be described. First, as discussed, secondary copies 116 can be stored in a different format (e.g., backup, archive, or other non-native format) than primary data 112. For this or other reasons, secondary copies 116 may not be directly useable by the applications 110 of the client computing device 102, e.g., via standard system calls or otherwise without modification, processing, or other intervention by the information management system 100.

Secondary copies 116 are also in some embodiments stored on a secondary storage device 108 that is inaccessible to the applications 110 running on the client computing devices 102 (and/or hosted services). Some secondary copies 116 may be “offline copies,” in that they are not readily available (e.g., not mounted to tape or disk). Offline copies can include copies of data that the information management system 100 can access without human intervention (e.g., tapes within an automated tape library, but not yet mounted in a drive), and copies that the information management system 100 can access only with at least some human intervention (e.g., tapes located at an offsite storage site).

The Use of Intermediate Devices for Creating Secondary Copies

Creating secondary copies can be a challenging task. For instance, there can be hundreds or thousands of client computing devices 102 continually generating large volumes of primary data 112 to be protected. Also, there can be significant overhead involved in the creation of secondary copies 116. Moreover, secondary storage devices 108 may be special purpose components, and interacting with them can require specialized intelligence.

In some cases, the client computing devices 102 interact directly with the secondary storage device 108 to create the secondary copies 116. However, in view of the factors described above, this approach can negatively impact the ability of the client computing devices 102 to serve the applications 110 and produce primary data 112. Further, the client computing devices 102 may not be optimized for interaction with the secondary storage devices 108.

Thus, in some embodiments, the information management system 100 includes one or more software and/or hardware components which generally act as intermediaries between the client computing devices 102 and the secondary storage devices 108. In addition to off-loading certain responsibilities from the client computing devices 102, these intermediate components can provide other benefits. For instance, as discussed further below with respect to FIG. 1D, distributing some of the work involved in creating secondary copies 116 can enhance scalability.

The intermediate components can include one or more secondary storage computing devices 106 as shown in FIG. 1A and/or one or more media agents, which can be software modules operating on corresponding secondary storage computing devices 106 (or other appropriate computing devices). Media agents are discussed below (e.g., with respect to FIGS. 1C-1E).

The secondary storage computing device(s) 106 can comprise any of the computing devices described above, without limitation. In some cases, the secondary storage computing device(s) 106 include specialized hardware and/or software componentry for interacting with the secondary storage devices 108.

To create a secondary copy 116 involving the copying of data from the primary storage subsystem 117 to the secondary storage subsystem 118, the client computing device 102 in some embodiments communicates the primary data 112 to be copied (or a processed version thereof) to the designated secondary storage computing device 106, via the communication pathway 114. The secondary storage computing device 106 in turn conveys the received data (or a processed version thereof) to the secondary storage device 108. In some such configurations, the communication pathway 114 between the client computing device 102 and the secondary storage computing device 106 comprises a portion of a LAN, WAN or SAN. In other cases, at least some client computing devices 102 communicate directly with the secondary storage devices 108 (e.g., via Fibre Channel or SCSI connections). In some other cases, one or more secondary copies 116 are created from existing secondary copies, such as in the case of an auxiliary copy operation, described in greater detail below.

Exemplary Primary Data and an Exemplary Secondary Copy

FIG. 1B is a detailed view showing some specific examples of primary data stored on the primary storage device(s) 104 and secondary copy data stored on the secondary storage device(s) 108, with other components in the system removed for the purposes of illustration. Stored on the primary storage device(s) 104 are primary data objects including word processing documents 119A-B, spreadsheets 120, presentation documents 122, video files 124, image files 126, email mailboxes 128 (and corresponding email messages 129A-C), html/xml or other types of markup language files 130, databases 132 and corresponding tables or other data structures 133A-133C).

Some or all primary data objects are associated with corresponding metadata (e.g., “Meta1-11”), which may include file system metadata and/or application specific metadata. Stored on the secondary storage device(s) 108 are secondary copy data objects 134A-C which may include copies of or otherwise represent corresponding primary data objects and metadata.

As shown, the secondary copy data objects 134A-C can individually represent more than one primary data object. For example, secondary copy data object 134A represents three separate primary data objects 133C, 122, and 129C (represented as 133C′, 122′, and 129C′, respectively, and accompanied by the corresponding metadata Meta11, Meta3, and Meta8, respectively). Moreover, as indicated by the prime mark (′), a secondary copy object may store a representation of a primary data object and/or metadata differently than the original format, e.g., in a compressed, encrypted, deduplicated, or other modified format. Likewise, secondary data object 134B represents primary data objects 120, 133B, and 119A as 120′, 133B′, and 119A′, respectively and accompanied by corresponding metadata Meta2, Meta10, and Meta1, respectively. Also, secondary data object 134C represents primary data objects 133A, 119B, and 129A as 133A′, 119B′, and 129A′, respectively, accompanied by corresponding metadata Meta9, Meta5, and Meta6, respectively.

Exemplary Information Management System Architecture

The information management system 100 can incorporate a variety of different hardware and software components, which can in turn be organized with respect to one another in many different configurations, depending on the embodiment. There are critical design choices involved in specifying the functional responsibilities of the components and the role of each component in the information management system 100. For instance, as will be discussed, such design choices can impact performance as well as the adaptability of the information management system 100 to data growth or other changing circumstances.

FIG. 1C shows an information management system 100 designed according to these considerations and which includes: storage manager 140, a centralized storage and/or information manager that is configured to perform certain control functions, one or more data agents 142 executing on the client computing device(s) 102 configured to process primary data 112, and one or more media agents 144 executing on the one or more secondary storage computing devices 106 for performing tasks involving the secondary storage devices 108. While distributing functionality amongst multiple computing devices can have certain advantages, in other contexts it can be beneficial to consolidate functionality on the same computing device. As such, in various other embodiments, one or more of the components shown in FIG. 1C as being implemented on separate computing devices are implemented on the same computing device. In one configuration, a storage manager 140, one or more data agents 142, and one or more media agents 144 are all implemented on the same computing device. In another embodiment, one or more data agents 142 and one or more media agents 144 are implemented on the same computing device, while the storage manager 140 is implemented on a separate computing device, etc. without limitation.

Storage Manager

As noted, the number of components in the information management system 100 and the amount of data under management can be quite large. Managing the components and data is therefore a significant task, and a task that can grow in an often unpredictable fashion as the quantity of components and data scale to meet the needs of the organization. For these and other reasons, according to certain embodiments, responsibility for controlling the information management system 100, or at least a significant portion of that responsibility, is allocated to the storage manager 140. By distributing control functionality in this manner, the storage manager 140 can be adapted independently according to changing circumstances. Moreover, a computing device for hosting the storage manager 140 can be selected to best suit the functions of the storage manager 140. These and other advantages are described in further detail below with respect to FIG. 1D.

The storage manager 140 may be a software module or other application, which, in some embodiments operates in conjunction with one or more associated data structures, e.g., a dedicated database (e.g., management database 146). In some embodiments, storage manager 140 is a computing device comprising circuitry for executing computer instructions and performs the functions described herein. The storage manager generally initiates, performs, coordinates and/or controls storage and other information management operations performed by the information management system 100, e.g., to protect and control the primary data 112 and secondary copies 116 of data and metadata. In general, storage manager 100 may be said to manage information management system 100, which includes managing the constituent components, e.g., data agents and media agents, etc.

As shown by the dashed arrowed lines 114 in FIG. 1C, the storage manager 140 may communicate with and/or control some or all elements of the information management system 100, such as the data agents 142 and media agents 144. Thus, in certain embodiments, control information originates from the storage manager 140 and status reporting is transmitted to storage manager 140 by the various managed components, whereas payload data and payload metadata is generally communicated between the data agents 142 and the media agents 144 (or otherwise between the client computing device(s) 102 and the secondary storage computing device(s) 106), e.g., at the direction of and under the management of the storage manager 140. Control information can generally include parameters and instructions for carrying out information management operations, such as, without limitation, instructions to perform a task associated with an operation, timing information specifying when to initiate a task associated with an operation, data path information specifying what components to communicate with or access in carrying out an operation, and the like. Payload data, on the other hand, can include the actual data involved in the storage operation, such as content data written to a secondary storage device 108 in a secondary copy operation. Payload metadata can include any of the types of metadata described herein, and may be written to a storage device along with the payload content data (e.g., in the form of a header).

In other embodiments, some information management operations are controlled by other components in the information management system 100 (e.g., the media agent(s) 144 or data agent(s) 142), instead of or in combination with the storage manager 140.

According to certain embodiments, the storage manager 140 provides one or more of the following functions:

-   -   initiating execution of secondary copy operations;     -   managing secondary storage devices 108 and inventory/capacity of         the same;     -   reporting, searching, and/or classification of data in the         information management system 100;     -   allocating secondary storage devices 108 for secondary storage         operations;     -   monitoring completion of and providing status reporting related         to secondary storage operations;     -   tracking age information relating to secondary copies 116,         secondary storage devices 108, and comparing the age information         against retention guidelines;     -   tracking movement of data within the information management         system 100;     -   tracking logical associations between components in the         information management system 100;     -   protecting metadata associated with the information management         system 100; and     -   implementing operations management functionality.

The storage manager 140 may maintain a database 146 (or “storage manager database 146” or “management database 146”) of management-related data and information management policies 148. The database 146 may include a management index 150 (or “index 150”) or other data structure that stores logical associations between components of the system, user preferences and/or profiles (e.g., preferences regarding encryption, compression, or deduplication of primary or secondary copy data, preferences regarding the scheduling, type, or other aspects of primary or secondary copy or other operations, mappings of particular information management users or user accounts to certain computing devices or other components, etc.), management tasks, media containerization, or other useful data. For example, the storage manager 140 may use the index 150 to track logical associations between media agents 144 and secondary storage devices 108 and/or movement of data from primary storage devices 104 to secondary storage devices 108. For instance, the index 150 may store data associating a client computing device 102 with a particular media agent 144 and/or secondary storage device 108, as specified in an information management policy 148 (e.g., a storage policy, which is defined in more detail below).

Administrators and other people may be able to configure and initiate certain information management operations on an individual basis. But while this may be acceptable for some recovery operations or other relatively less frequent tasks, it is often not workable for implementing on-going organization-wide data protection and management. Thus, the information management system 100 may utilize information management policies 148 for specifying and executing information management operations (e.g., on an automated basis). Generally, an information management policy 148 can include a data structure or other information source that specifies a set of parameters (e.g., criteria and rules) associated with storage or other information management operations.

The storage manager database 146 may maintain the information management policies 148 and associated data, although the information management policies 148 can be stored in any appropriate location. For instance, an information management policy 148 such as a storage policy may be stored as metadata in a media agent database 152 or in a secondary storage device 108 (e.g., as an archive copy) for use in restore operations or other information management operations, depending on the embodiment. Information management policies 148 are described further below.

According to certain embodiments, the storage manager database 146 comprises a relational database (e.g., an SQL database) for tracking metadata, such as metadata associated with secondary copy operations (e.g., what client computing devices 102 and corresponding data were protected). This and other metadata may additionally be stored in other locations, such as at the secondary storage computing devices 106 or on the secondary storage devices 108, allowing data recovery without the use of the storage manager 140 in some cases.

As shown, the storage manager 140 may include a jobs agent 156, a user interface 158, and a management agent 154, all of which may be implemented as interconnected software modules or application programs.

The jobs agent 156 in some embodiments initiates, controls, and/or monitors the status of some or all storage or other information management operations previously performed, currently being performed, or scheduled to be performed by the information management system 100. For instance, the jobs agent 156 may access information management policies 148 to determine when and how to initiate and control secondary copy and other information management operations, as will be discussed further.

The user interface 158 may include information processing and display software, such as a graphical user interface (“GUI”), an application program interface (“API”), or other interactive interface(s) through which users and system processes can retrieve information about the status of information management operations (e.g., storage operations) or issue instructions to the information management system 100 and its constituent components. Via the user interface 158, users may optionally issue instructions to the components in the information management system 100 regarding performance of storage and recovery operations. For example, a user may modify a schedule concerning the number of pending secondary copy operations. As another example, a user may employ the GUI to view the status of pending storage operations or to monitor the status of certain components in the information management system 100 (e.g., the amount of capacity left in a storage device).

An “information management cell” (or “storage operation cell” or “cell”) may generally include a logical and/or physical grouping of a combination of hardware and software components associated with performing information management operations on electronic data, typically one storage manager 140 and at least one client computing device 102 (comprising data agent(s) 142) and at least one media agent 144. For instance, the components shown in FIG. 1C may together form an information management cell. Multiple cells may be organized hierarchically. With this configuration, cells may inherit properties from hierarchically superior cells or be controlled by other cells in the hierarchy (automatically or otherwise). Alternatively, in some embodiments, cells may inherit or otherwise be associated with information management policies, preferences, information management metrics, or other properties or characteristics according to their relative position in a hierarchy of cells. Cells may also be delineated and/or organized hierarchically according to function, geography, architectural considerations, or other factors useful or desirable in performing information management operations. A first cell may represent a geographic segment of an enterprise, such as a Chicago office, and a second cell may represent a different geographic segment, such as a New York office. Other cells may represent departments within a particular office. Where delineated by function, a first cell may perform one or more first types of information management operations (e.g., one or more first types of secondary or other copies), and a second cell may perform one or more second types of information management operations (e.g., one or more second types of secondary or other copies).

The storage manager 140 may also track information that permits it to select, designate, or otherwise identify content indices, deduplication databases, or similar databases or resources or data sets within its information management cell (or another cell) to be searched in response to certain queries. Such queries may be entered by the user via interaction with the user interface 158. In general, the management agent 154 allows multiple information management cells to communicate with one another. For example, the information management system 100 in some cases may be one information management cell of a network of multiple cells adjacent to one another or otherwise logically related in a WAN or LAN. With this arrangement, the cells may be connected to one another through respective management agents 154.

For instance, the management agent 154 can provide the storage manager 140 with the ability to communicate with other components within the information management system 100 (and/or other cells within a larger information management system) via network protocols and application programming interfaces (“APIs”) including, e.g., HTTP, HTTPS, FTP, REST, virtualization software APIs, cloud service provider APIs, and hosted service provider APIs. Inter-cell communication and hierarchy is described in greater detail in e.g., U.S. Pat. Nos. 7,747,579 and 7,343,453, which are incorporated by reference herein.

Data Agents

As discussed, a variety of different types of applications 110 can operate on a given client computing device 102, including operating systems, database applications, e-mail applications, and virtual machines, just to name a few. And, as part of the process of creating and restoring secondary copies 116, the client computing devices 102 may be tasked with processing and preparing the primary data 112 from these various different applications 110. Moreover, the nature of the processing/preparation can differ across clients and application types, e.g., due to inherent structural and formatting differences among applications 110.

The one or more data agent(s) 142 are therefore advantageously configured in some embodiments to assist in the performance of information management operations based on the type of data that is being protected, at a client-specific and/or application-specific level.

The data agent 142 may be a software module or component that is generally responsible for managing, initiating, or otherwise assisting in the performance of information management operations in information management system 100, generally as directed by storage manager 140. For instance, the data agent 142 may take part in performing data storage operations such as the copying, archiving, migrating, and/or replicating of primary data 112 stored in the primary storage device(s) 104. The data agent 142 may receive control information from the storage manager 140, such as commands to transfer copies of data objects, metadata, and other payload data to the media agents 144.

In some embodiments, a data agent 142 may be distributed between the client computing device 102 and storage manager 140 (and any other intermediate components) or may be deployed from a remote location or its functions approximated by a remote process that performs some or all of the functions of data agent 142. In addition, a data agent 142 may perform some functions provided by a media agent 144, or may perform other functions such as encryption and deduplication.

As indicated, each data agent 142 may be specialized for a particular application 110, and the system can employ multiple application-specific data agents 142, each of which may perform information management operations (e.g., perform backup, migration, and data recovery) associated with a different application 110. For instance, different individual data agents 142 may be designed to handle Microsoft Exchange data, Lotus Notes data, Microsoft Windows file system data, Microsoft Active Directory Objects data, SQL Server data, SharePoint data, Oracle database data, SAP database data, virtual machines and/or associated data, and other types of data.

A file system data agent, for example, may handle data files and/or other file system information. If a client computing device 102 has two or more types of data, a specialized data agent 142 may be used for each data type to copy, archive, migrate, and restore the client computing device 102 data. For example, to backup, migrate, and/or restore all of the data on a Microsoft Exchange server, the client computing device 102 may use a Microsoft Exchange Mailbox data agent 142 to back up the Exchange mailboxes, a Microsoft Exchange Database data agent 142 to back up the Exchange databases, a Microsoft Exchange Public Folder data agent 142 to back up the Exchange Public Folders, and a Microsoft Windows File System data agent 142 to back up the file system of the client computing device 102. In such embodiments, these specialized data agents 142 may be treated as four separate data agents 142 even though they operate on the same client computing device 102.

Other embodiments may employ one or more generic data agents 142 that can handle and process data from two or more different applications 110, or that can handle and process multiple data types, instead of or in addition to using specialized data agents 142. For example, one generic data agent 142 may be used to back up, migrate and restore Microsoft Exchange Mailbox data and Microsoft Exchange Database data while another generic data agent may handle Microsoft Exchange Public Folder data and Microsoft Windows File System data.

Each data agent 142 may be configured to access data and/or metadata stored in the primary storage device(s) 104 associated with the data agent 142 and process the data as appropriate. For example, during a secondary copy operation, the data agent 142 may arrange or assemble the data and metadata into one or more files having a certain format (e.g., a particular backup or archive format) before transferring the file(s) to a media agent 144 or other component. The file(s) may include a list of files or other metadata. Each data agent 142 can also assist in restoring data or metadata to primary storage devices 104 from a secondary copy 116. For instance, the data agent 142 may operate in conjunction with the storage manager 140 and one or more of the media agents 144 to restore data from secondary storage device(s) 108.

Media Agents

As indicated above with respect to FIG. 1A, off-loading certain responsibilities from the client computing devices 102 to intermediate components such as the media agent(s) 144 can provide a number of benefits including improved client computing device 102 operation, faster secondary copy operation performance, and enhanced scalability. In one specific example which will be discussed below in further detail, the media agent 144 can act as a local cache of copied data and/or metadata that it has stored to the secondary storage device(s) 108, providing improved restore capabilities.

Generally speaking, a media agent 144 may be implemented as a software module that manages, coordinates, and facilitates the transmission of data, as directed by the storage manager 140, between a client computing device 102 and one or more secondary storage devices 108. Whereas the storage manager 140 controls the operation of the information management system 100, the media agent 144 generally provides a portal to secondary storage devices 108. For instance, other components in the system interact with the media agents 144 to gain access to data stored on the secondary storage devices 108, whether it be for the purposes of reading, writing, modifying, or deleting data. Moreover, as will be described further, media agents 144 can generate and store information relating to characteristics of the stored data and/or metadata, or can generate and store other types of information that generally provides insight into the contents of the secondary storage devices 108.

Media agents 144 can comprise separate nodes in the information management system 100 (e.g., nodes that are separate from the client computing devices 102, storage manager 140, and/or secondary storage devices 108). In general, a node within the information management system 100 can be a logically and/or physically separate component, and in some cases is a component that is individually addressable or otherwise identifiable. In addition, each media agent 144 may operate on a dedicated secondary storage computing device 106 in some cases, while in other embodiments a plurality of media agents 144 operate on the same secondary storage computing device 106.

A media agent 144 (and corresponding media agent database 152) may be considered to be “associated with” a particular secondary storage device 108 if that media agent 144 is capable of one or more of: routing and/or storing data to the particular secondary storage device 108, coordinating the routing and/or storing of data to the particular secondary storage device 108, retrieving data from the particular secondary storage device 108, coordinating the retrieval of data from a particular secondary storage device 108, and modifying and/or deleting data retrieved from the particular secondary storage device 108.

While media agent(s) 144 are generally associated with one or more secondary storage devices 108, one or more media agents 144 in certain embodiments are physically separate from the secondary storage devices 108. For instance, the media agents 144 may operate on secondary storage computing devices 106 having different housings or packages than the secondary storage devices 108. In one example, a media agent 144 operates on a first server computer and is in communication with a secondary storage device(s) 108 operating in a separate, rack-mounted RAID-based system.

Where the information management system 100 includes multiple media agents 144 (see, e.g., FIG. 1D), a first media agent 144 may provide failover functionality for a second, failed media agent 144. In addition, media agents 144 can be dynamically selected for storage operations to provide load balancing. Failover and load balancing are described in greater detail below.

In operation, a media agent 144 associated with a particular secondary storage device 108 may instruct the secondary storage device 108 to perform an information management operation. For instance, a media agent 144 may instruct a tape library to use a robotic arm or other retrieval means to load or eject a certain storage media, and to subsequently archive, migrate, or retrieve data to or from that media, e.g., for the purpose of restoring the data to a client computing device 102. As another example, a secondary storage device 108 may include an array of hard disk drives or solid state drives organized in a RAID configuration, and the media agent 144 may forward a logical unit number (LUN) and other appropriate information to the array, which uses the received information to execute the desired storage operation. The media agent 144 may communicate with a secondary storage device 108 via a suitable communications link, such as a SCSI or Fiber Channel link.

As shown, each media agent 144 may maintain an associated media agent database 152. The media agent database 152 may be stored in a disk or other storage device (not shown) that is local to the secondary storage computing device 106 on which the media agent 144 operates. In other cases, the media agent database 152 is stored remotely from the secondary storage computing device 106.

The media agent database 152 can include, among other things, an index 153 (see, e.g., FIG. 1C), which comprises information generated during secondary copy operations and other storage or information management operations. The index 153 provides a media agent 144 or other component with a fast and efficient mechanism for locating secondary copies 116 or other data stored in the secondary storage devices 108. In some cases, the index 153 does not form a part of and is instead separate from the media agent database 152.

A media agent index 153 or other data structure associated with the particular media agent 144 may include information about the stored data. For instance, for each secondary copy 116, the index 153 may include metadata such as a list of the data objects (e.g., files/subdirectories, database objects, mailbox objects, etc.), a path to the secondary copy 116 on the corresponding secondary storage device 108, location information indicating where the data objects are stored in the secondary storage device 108, when the data objects were created or modified, etc. Thus, the index 153 includes metadata associated with the secondary copies 116 that is readily available for use without having to be first retrieved from the secondary storage device 108. In yet further embodiments, some or all of the information in index 153 may instead or additionally be stored along with the secondary copies of data in a secondary storage device 108. In some embodiments, the secondary storage devices 108 can include sufficient information to perform a “bare metal restore”, where the operating system of a failed client computing device 102 or other restore target is automatically rebuilt as part of a restore operation.

Because the index 153 maintained in the media agent database 152 may operate as a cache, it can also be referred to as “an index cache.” In such cases, information stored in the index cache 153 typically comprises data that reflects certain particulars about storage operations that have occurred relatively recently. After some triggering event, such as after a certain period of time elapses, or the index cache 153 reaches a particular size, the index cache 153 may be copied or migrated to a secondary storage device(s) 108. This information may need to be retrieved and uploaded back into the index cache 153 or otherwise restored to a media agent 144 to facilitate retrieval of data from the secondary storage device(s) 108. In some embodiments, the cached information may include format or containerization information related to archives or other files stored on the storage device(s) 108. In this manner, the index cache 153 allows for accelerated restores.

In some alternative embodiments the media agent 144 generally acts as a coordinator or facilitator of storage operations between client computing devices 102 and corresponding secondary storage devices 108, but does not actually write the data to the secondary storage device 108. For instance, the storage manager 140 (or the media agent 144) may instruct a client computing device 102 and secondary storage device 108 to communicate with one another directly. In such a case the client computing device 102 transmits the data directly or via one or more intermediary components to the secondary storage device 108 according to the received instructions, and vice versa. In some such cases, the media agent 144 may still receive, process, and/or maintain metadata related to the storage operations. Moreover, in these embodiments, the payload data can flow through the media agent 144 for the purposes of populating the index cache 153 maintained in the media agent database 152, but not for writing to the secondary storage device 108.

The media agent 144 and/or other components such as the storage manager 140 may in some cases incorporate additional functionality, such as data classification, content indexing, deduplication, encryption, compression, and the like. Further details regarding these and other functions are described below.

Distributed, Scalable Architecture

As described, certain functions of the information management system 100 can be distributed amongst various physical and/or logical components in the system. For instance, one or more of the storage manager 140, data agents 142, and media agents 144 may operate on computing devices that are physically separate from one another. This architecture can provide a number of benefits.

For instance, hardware and software design choices for each distributed component can be targeted to suit its particular function. The secondary computing devices 106 on which the media agents 144 operate can be tailored for interaction with associated secondary storage devices 108 and provide fast index cache operation, among other specific tasks. Similarly, the client computing device(s) 102 can be selected to effectively service the applications 110 thereon, in order to efficiently produce and store primary data 112.

Moreover, in some cases, one or more of the individual components in the information management system 100 can be distributed to multiple, separate computing devices. As one example, for large file systems where the amount of data stored in the management database 146 is relatively large, the database 146 may be migrated to or otherwise reside on a specialized database server (e.g., an SQL server) separate from a server that implements the other functions of the storage manager 140. This distributed configuration can provide added protection because the database 146 can be protected with standard database utilities (e.g., SQL log shipping or database replication) independent from other functions of the storage manager 140. The database 146 can be efficiently replicated to a remote site for use in the event of a disaster or other data loss at the primary site. Or the database 146 can be replicated to another computing device within the same site, such as to a higher performance machine in the event that a storage manager host device can no longer service the needs of a growing information management system 100.

The distributed architecture also provides both scalability and efficient component utilization. FIG. 1D shows an embodiment of the information management system 100 including a plurality of client computing devices 102 and associated data agents 142 as well as a plurality of secondary storage computing devices 106 and associated media agents 144.

Additional components can be added or subtracted based on the evolving needs of the information management system 100. For instance, depending on where bottlenecks are identified, administrators can add additional client computing devices 102, secondary storage computing devices 106 (and corresponding media agents 144), and/or secondary storage devices 108. Moreover, where multiple fungible components are available, load balancing can be implemented to dynamically address identified bottlenecks. As an example, the storage manager 140 may dynamically select which media agents 144 and/or secondary storage devices 108 to use for storage operations based on a processing load analysis of the media agents 144 and/or secondary storage devices 108, respectively.

Moreover, each client computing device 102 in some embodiments can communicate with, among other components, any of the media agents 144, e.g., as directed by the storage manager 140. And each media agent 144 may be able to communicate with, among other components, any of the secondary storage devices 108, e.g., as directed by the storage manager 140. Thus, operations can be routed to the secondary storage devices 108 in a dynamic and highly flexible manner, to provide load balancing, failover, and the like. Further examples of scalable systems capable of dynamic storage operations, and of systems capable of performing load balancing and fail over are provided in U.S. Pat. No. 7,246,207, which is incorporated by reference herein.

In alternative configurations, certain components are not distributed and may instead reside and execute on the same computing device. For example, in some embodiments, one or more data agents 142 and the storage manager 140 operate on the same client computing device 102. In another embodiment, one or more data agents 142 and one or more media agents 144 operate on a single computing device.

Exemplary Types of Information Management Operations

In order to protect and leverage stored data, the information management system 100 can be configured to perform a variety of information management operations. As will be described, these operations can generally include secondary copy and other data movement operations, processing and data manipulation operations, analysis, reporting, and management operations. The operations described herein may be performed on any type of computing device, e.g., between two computers connected via a LAN, to a mobile client telecommunications device connected to a server via a WLAN, to any manner of client computing device coupled to a cloud storage target, etc., without limitation.

Data Movement Operations

Data movement operations according to certain embodiments are generally operations that involve the copying or migration of data (e.g., payload data) between different locations in the information management system 100 in an original/native and/or one or more different formats. For example, data movement operations can include operations in which stored data is copied, migrated, or otherwise transferred from one or more first storage devices to one or more second storage devices, such as from primary storage device(s) 104 to secondary storage device(s) 108, from secondary storage device(s) 108 to different secondary storage device(s) 108, from secondary storage devices 108 to primary storage devices 104, or from primary storage device(s) 104 to different primary storage device(s) 104.

Data movement operations can include by way of example, backup operations, archive operations, information lifecycle management operations such as hierarchical storage management operations, replication operations (e.g., continuous data replication operations), snapshot operations, deduplication or single-instancing operations, auxiliary copy operations, and the like. As will be discussed, some of these operations involve the copying, migration or other movement of data, without actually creating multiple, distinct copies. Nonetheless, some or all of these operations are referred to as “copy” operations for simplicity.

Backup Operations

A backup operation creates a copy of a version of data (e.g., one or more files or other data units) in primary data 112 at a particular point in time. Each subsequent backup copy may be maintained independently of the first. Further, a backup copy in some embodiments is generally stored in a form that is different than the native format, e.g., a backup format. This can be in contrast to the version in primary data 112 from which the backup copy is derived, and which may instead be stored in a native format of the source application(s) 110. In various cases, backup copies can be stored in a format in which the data is compressed, encrypted, deduplicated, and/or otherwise modified from the original application format. For example, a backup copy may be stored in a backup format that facilitates compression and/or efficient long-term storage.

Backup copies can have relatively long retention periods as compared to primary data 112, and may be stored on media with slower retrieval times than primary data 112 and certain other types of secondary copies 116. On the other hand, backups may have relatively shorter retention periods than some other types of secondary copies 116, such as archive copies (described below). Backups may sometimes be stored at on offsite location.

Backup operations can include full backups, differential backups, incremental backups, “synthetic full” backups, and/or creating a “reference copy.” A full backup (or “standard full backup”) in some embodiments is generally a complete image of the data to be protected. However, because full backup copies can consume a relatively large amount of storage, it can be useful to use a full backup copy as a baseline and only store changes relative to the full backup copy for subsequent backup copies.

For instance, a differential backup operation (or cumulative incremental backup operation) tracks and stores changes that have occurred since the last full backup. Differential backups can grow quickly in size, but can provide relatively efficient restore times because a restore can be completed in some cases using only the full backup copy and the latest differential copy.

An incremental backup operation generally tracks and stores changes since the most recent backup copy of any type, which can greatly reduce storage utilization. In some cases, however, restore times can be relatively long in comparison to full or differential backups because completing a restore operation may involve accessing a full backup in addition to multiple incremental backups.

Synthetic full backups generally consolidate data without directly backing up data from the client computing device. A synthetic full backup is created from the most recent full backup (i.e., standard or synthetic) and subsequent incremental and/or differential backups. The resulting synthetic full backup is identical to what would have been created had the last backup for the subclient been a standard full backup. Unlike standard full, incremental, and differential backups, a synthetic full backup does not actually transfer data from a client computer to the backup media, because it operates as a backup consolidator. A synthetic full backup extracts the index data of each participating subclient. Using this index data and the previously backed up user data images, it builds new full backup images, one for each subclient. The new backup images consolidate the index and user data stored in the related incremental, differential, and previous full backups, in some embodiments creating an archive file at the subclient level.

Any of the above types of backup operations can be at the volume-level, file-level, or block-level. Volume level backup operations generally involve the copying of a data volume (e.g., a logical disk or partition) as a whole. In a file-level backup, the information management system 100 may generally track changes to individual files, and includes copies of files in the backup copy. In the case of a block-level backup, files are broken into constituent blocks, and changes are tracked at the block-level. Upon restore, the information management system 100 reassembles the blocks into files in a transparent fashion.

Far less data may actually be transferred and copied to the secondary storage devices 108 during a file-level copy than a volume-level copy. Likewise, a block-level copy may involve the transfer of less data than a file-level copy, resulting in faster execution times. However, restoring a relatively higher-granularity copy can result in longer restore times. For instance, when restoring a block-level copy, the process of locating constituent blocks can sometimes result in longer restore times as compared to file-level backups. Similar to backup operations, the other types of secondary copy operations described herein can also be implemented at either the volume-level, file-level, or block-level.

For example, in some embodiments, a reference copy may comprise copy(ies) of selected objects from backed up data, typically to help organize data by keeping contextual information from multiple sources together, and/or help retain specific data for a longer period of time, such as for legal hold needs. A reference copy generally maintains data integrity, and when the data is restored, it may be viewed in the same format as the source data. In some embodiments, a reference copy is based on a specialized client, individual subclient and associated information management policies (e.g., storage policy, retention policy, etc.) that are administered within information management system 100.

Archive Operations

Because backup operations generally involve maintaining a version of the copied data in primary data 112 and also maintaining backup copies in secondary storage device(s) 108, they can consume significant storage capacity. To help reduce storage consumption, an archive operation according to certain embodiments creates a secondary copy 116 by both copying and removing source data. Or, seen another way, archive operations can involve moving some or all of the source data to the archive destination. Thus, data satisfying criteria for removal (e.g., data of a threshold age or size) may be removed from source storage. The source data may be primary data 112 or a secondary copy 116, depending on the situation. As with backup copies, archive copies can be stored in a format in which the data is compressed, encrypted, deduplicated, and/or otherwise modified from the format of the original application or source copy. In addition, archive copies may be retained for relatively long periods of time (e.g., years) and, in some cases, are never deleted. Archive copies are generally retained for longer periods of time than backup copies, for example. In certain embodiments, archive copies may be made and kept for extended periods in order to meet compliance regulations.

Moreover, when primary data 112 is archived, in some cases the corresponding primary data 112 or a portion thereof is deleted when creating the archive copy. Thus, archiving can serve the purpose of freeing up space in the primary storage device(s) 104 and easing the demand on computational resources on client computing device 102. Similarly, when a secondary copy 116 is archived, the secondary copy 116 may be deleted, and an archive copy can therefore serve the purpose of freeing up space in secondary storage device(s) 108. In contrast, source copies often remain intact when creating backup copies. Examples of compatible data archiving operations are provided in U.S. Pat. No. 7,107,298, which is incorporated by reference herein.

Snapshot Operations

Snapshot operations can provide a relatively lightweight, efficient mechanism for protecting data. From an end-user viewpoint, a snapshot may be thought of as an “instant” image of the primary data 112 at a given point in time, and may include state and/or status information relative to an application that creates/manages the primary data. In one embodiment, a snapshot may generally capture the directory structure of an object in primary data 112 such as a file or volume or other data set at a particular moment in time and may also preserve file attributes and contents. A snapshot in some cases is created relatively quickly, e.g., substantially instantly, using a minimum amount of file space, but may still function as a conventional file system backup.

A “hardware snapshot” (or “hardware-based snapshot”) operation can be a snapshot operation where a target storage device (e.g., a primary storage device 104 or a secondary storage device 108) performs the snapshot operation in a self-contained fashion, substantially independently, using hardware, firmware and/or software operating on the storage device itself. For instance, the storage device may be capable of performing snapshot operations upon request, generally without intervention or oversight from any of the other components in the information management system 100. In this manner, hardware snapshots can off-load other components of information management system 100 from processing involved in snapshot creation and management.

A “software snapshot” (or “software-based snapshot”) operation, on the other hand, can be a snapshot operation in which one or more other components in information management system 100 (e.g., client computing devices 102, data agents 142, etc.) implement a software layer that manages the snapshot operation via interaction with the target storage device. For instance, the component executing the snapshot management software layer may derive a set of pointers and/or data that represents the snapshot. The snapshot management software layer may then transmit the same to the target storage device, along with appropriate instructions for writing the snapshot.

Some types of snapshots do not actually create another physical copy of all the data as it existed at the particular point in time, but may simply create pointers that are able to map files and directories to specific memory locations (e.g., to specific disk blocks) where the data resides, as it existed at the particular point in time. For example, a snapshot copy may include a set of pointers derived from the file system or from an application. In some other cases, the snapshot may be created at the block-level, such that creation of the snapshot occurs without awareness of the file system. Each pointer points to a respective stored data block, so that collectively, the set of pointers reflect the storage location and state of the data object (e.g., file(s) or volume(s) or data set(s)) at a particular point in time when the snapshot copy was created.

An initial snapshot may use only a small amount of disk space needed to record a mapping or other data structure representing or otherwise tracking the blocks that correspond to the current state of the file system. Additional disk space is usually required only when files and directories are modified later on. Furthermore, when files are modified, typically only the pointers which map to blocks are copied, not the blocks themselves. In some embodiments, for example in the case of “copy-on-write” snapshots, when a block changes in primary storage, the block is copied to secondary storage or cached in primary storage before the block is overwritten in primary storage, and the pointer to that block changed to reflect the new location of that block. The snapshot mapping of file system data may also be updated to reflect the changed block(s) at that particular point in time. In some other cases, a snapshot includes a full physical copy of all or substantially all of the data represented by the snapshot. Further examples of snapshot operations are provided in U.S. Pat. No. 7,529,782, which is incorporated by reference herein.

A snapshot copy in many cases can be made quickly and without significantly impacting primary computing resources because large amounts of data need not be copied or moved. In some embodiments, a snapshot may exist as a virtual file system, parallel to the actual file system. Users in some cases gain read-only access to the record of files and directories of the snapshot. By electing to restore primary data 112 from a snapshot taken at a given point in time, users may also return the current file system to the state of the file system that existed when the snapshot was taken.

Replication Operations

Another type of secondary copy operation is a replication operation. Some types of secondary copies 116 are used to periodically capture images of primary data 112 at particular points in time (e.g., backups, archives, and snapshots). However, it can also be useful for recovery purposes to protect primary data 112 in a more continuous fashion, by replicating the primary data 112 substantially as changes occur. In some cases a replication copy can be a mirror copy, for instance, where changes made to primary data 112 are mirrored or substantially immediately copied to another location (e.g., to secondary storage device(s) 108). By copying each write operation to the replication copy, two storage systems are kept synchronized or substantially synchronized so that they are virtually identical at approximately the same time. Where entire disk volumes are mirrored, however, mirroring can require significant amount of storage space and utilizes a large amount of processing resources.

According to some embodiments storage operations are performed on replicated data that represents a recoverable state, or “known good state” of a particular application running on the source system. For instance, in certain embodiments, known good replication copies may be viewed as copies of primary data 112. This feature allows the system to directly access, copy, restore, backup or otherwise manipulate the replication copies as if the data were the “live” primary data 112. This can reduce access time, storage utilization, and impact on source applications 110, among other benefits. Based on known good state information, the information management system 100 can replicate sections of application data that represent a recoverable state rather than rote copying of blocks of data. Examples of compatible replication operations (e.g., continuous data replication) are provided in U.S. Pat. No. 7,617,262, which is incorporated by reference herein.

Deduplication/Single-Instancing Operations

Another type of data movement operation is deduplication or single-instance storage, which is useful to reduce the amount of non-primary data. For instance, some or all of the above-described secondary storage operations can involve deduplication in some fashion. New data is read, broken down into portions (e.g., sub-file level blocks, files, etc.) of a selected granularity, compared with blocks that are already in secondary storage, and only the new blocks are stored. Blocks that already exist are represented as pointers to the already stored data.

In order to streamline the comparison process, the information management system 100 may calculate and/or store signatures (e.g., hashes or cryptographically unique IDs) corresponding to the individual data blocks in a database and compare the signatures instead of comparing entire data blocks. In some cases, only a single instance of each element is stored, and deduplication operations may therefore be referred to interchangeably as “single-instancing” operations. Depending on the implementation, however, deduplication or single-instancing operations can store more than one instance of certain data blocks, but nonetheless significantly reduce data redundancy. Depending on the embodiment, deduplication blocks can be of fixed or variable length. Using variable length blocks can provide enhanced deduplication by responding to changes in the data stream, but can involve complex processing. In some cases, the information management system 100 utilizes a technique for dynamically aligning deduplication blocks (e.g., fixed-length blocks) based on changing content in the data stream, as described in U.S. Pat. No. 8,364,652, which is incorporated by reference herein.

The information management system 100 can perform deduplication in a variety of manners at a variety of locations in the information management system 100. For instance, in some embodiments, the information management system 100 implements “target-side” deduplication by deduplicating data (e.g., secondary copies 116) stored in the secondary storage devices 108. In some such cases, the media agents 144 are generally configured to manage the deduplication process. For instance, one or more of the media agents 144 maintain a corresponding deduplication database that stores deduplication information (e.g., datablock signatures). Examples of such a configuration are provided in U.S. Pat. Pub. No. 2012/0150826, which is incorporated by reference herein. Instead of or in combination with “target-side” deduplication, deduplication can also be performed on the “source-side” (or “client-side”), e.g., to reduce the amount of traffic between the media agents 144 and the client computing device(s) 102 and/or reduce redundant data stored in the primary storage devices 104. According to various implementations, one or more of the storage devices of the target-side and/or source-side of an operation can be cloud-based storage devices. Thus, the target-side and/or source-side deduplication can be cloud-based deduplication. In particular, as discussed previously, the storage manager 140 may communicate with other components within the information management system 100 via network protocols and cloud service provider APIs to facilitate cloud-based deduplication/single instancing. Examples of such deduplication techniques are provided in U.S. Pat. Pub. No. 2012/0150818, which is incorporated by reference herein. Some other compatible deduplication/single instancing techniques are described in U.S. Pat. Pub. Nos. 2006/0224846 and 2009/0319534, which are incorporated by reference herein.

Information Lifecycle Management and Hierarchical Storage Management Operations

In some embodiments, files and other data over their lifetime move from more expensive, quick access storage to less expensive, slower access storage. Operations associated with moving data through various tiers of storage are sometimes referred to as information lifecycle management (ILM) operations.

One type of ILM operation is a hierarchical storage management (HSM) operation. A HSM operation is generally an operation for automatically moving data between classes of storage devices, such as between high-cost and low-cost storage devices. For instance, an HSM operation may involve movement of data from primary storage devices 104 to secondary storage devices 108, or between tiers of secondary storage devices 108. With each tier, the storage devices may be progressively relatively cheaper, have relatively slower access/restore times, etc. For example, movement of data between tiers may occur as data becomes less important over time.

In some embodiments, an HSM operation is similar to an archive operation in that creating an HSM copy may (though not always) involve deleting some of the source data, e.g., according to one or more criteria related to the source data. For example, an HSM copy may include data from primary data 112 or a secondary copy 116 that is larger than a given size threshold or older than a given age threshold and that is stored in a backup format.

Often, and unlike some types of archive copies, HSM data that is removed or aged from the source is replaced by a logical reference pointer or stub. The reference pointer or stub can be stored in the primary storage device 104 (or other source storage device, such as a secondary storage device 108) to replace the deleted source data and to point to or otherwise indicate the new location in a secondary storage device 108.

According to one example, files are generally moved between higher and lower cost storage depending on how often the files are accessed. When a user requests access to the HSM data that has been removed or migrated, the information management system 100 uses the stub to locate the data and may make recovery of the data appear transparent, even though the HSM data may be stored at a location different from other source data. In this manner, the data appears to the user (e.g., in file system browsing windows and the like) as if it still resides in the source location (e.g., in a primary storage device 104). The stub may also include some metadata associated with the corresponding data, so that a file system and/or application can provide some information about the data object and/or a limited-functionality version (e.g., a preview) of the data object.

An HSM copy may be stored in a format other than the native application format (e.g., where the data is compressed, encrypted, deduplicated, and/or otherwise modified from the original native application format). In some cases, copies which involve the removal of data from source storage and the maintenance of stub or other logical reference information on source storage may be referred to generally as “on-line archive copies”. On the other hand, copies which involve the removal of data from source storage without the maintenance of stub or other logical reference information on source storage may be referred to as “off-line archive copies”. Examples of HSM and ILM techniques are provided in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.

Auxiliary Copy and Disaster Recovery Operations

An auxiliary copy is generally a copy operation in which a copy is created of an existing secondary copy 116. For instance, an initial secondary copy 116 may be generated using or otherwise be derived from primary data 112 (or other data residing in the secondary storage subsystem 118), whereas an auxiliary copy is generated from the initial secondary copy 116. Auxiliary copies can be used to create additional standby copies of data and may reside on different secondary storage devices 108 than the initial secondary copies 116. Thus, auxiliary copies can be used for recovery purposes if initial secondary copies 116 become unavailable. Exemplary compatible auxiliary copy techniques are described in further detail in U.S. Pat. No. 8,230,195, which is incorporated by reference herein.

The information management system 100 may also perform disaster recovery operations that make or retain disaster recovery copies, often as secondary, high-availability disk copies. The information management system 100 may create secondary disk copies and store the copies at disaster recovery locations using auxiliary copy or replication operations, such as continuous data replication technologies. Depending on the particular data protection goals, disaster recovery locations can be remote from the client computing devices 102 and primary storage devices 104, remote from some or all of the secondary storage devices 108, or both.

Data Analysis, Reporting, and Management Operations

Data analysis, reporting, and management operations can be different than data movement operations in that they do not necessarily involve the copying, migration or other transfer of data (e.g., primary data 112 or secondary copies 116) between different locations in the system. For instance, data analysis operations may involve processing (e.g., offline processing) or modification of already stored primary data 112 and/or secondary copies 116. However, in some embodiments data analysis operations are performed in conjunction with data movement operations. Some data analysis operations include content indexing operations and classification operations which can be useful in leveraging the data under management to provide enhanced search and other features. Other data analysis operations such as compression and encryption can provide data reduction and security benefits, respectively.

Classification Operations/Content Indexing

In some embodiments, the information management system 100 analyzes and indexes characteristics, content, and metadata associated with the primary data 112 and/or secondary copies 116. The content indexing can be used to identify files or other data objects having pre-defined content (e.g., user-defined keywords or phrases, other keywords/phrases that are not defined by a user, etc.), and/or metadata (e.g., email metadata such as “to”, “from”, “cc”, “bcc”, attachment name, received time, etc.).

The information management system 100 generally organizes and catalogues the results in a content index, which may be stored within the media agent database 152, for example. The content index can also include the storage locations of (or pointer references to) the indexed data in the primary data 112 or secondary copies 116, as appropriate. The results may also be stored, in the form of a content index database or otherwise, elsewhere in the information management system 100 (e.g., in the primary storage devices 104, or in the secondary storage device 108). Such index data provides the storage manager 140 or another component with an efficient mechanism for locating primary data 112 and/or secondary copies 116 of data objects that match particular criteria.

For instance, search criteria can be specified by a user through user interface 158 of the storage manager 140. In some cases, the information management system 100 analyzes data and/or metadata in secondary copies 116 to create an “off-line” content index, without significantly impacting the performance of the client computing devices 102. Depending on the embodiment, the system can also implement “on-line” content indexing, e.g., of primary data 112. Examples of compatible content indexing techniques are provided in U.S. Pat. No. 8,170,995, which is incorporated by reference herein.

One or more components can be configured to scan data and/or associated metadata for classification purposes to populate a database (or other data structure) of information, which can be referred to as a “data classification database” or a “metabase”. Depending on the embodiment, the data classification database(s) can be organized in a variety of different ways, including centralization, logical sub-divisions, and/or physical sub-divisions. For instance, one or more centralized data classification databases may be associated with different subsystems or tiers within the information management system 100. As an example, there may be a first centralized metabase associated with the primary storage subsystem 117 and a second centralized metabase associated with the secondary storage subsystem 118. In other cases, there may be one or more metabases associated with individual components, e.g., client computing devices 102 and/or media agents 144. In some embodiments, a data classification database (metabase) may reside as one or more data structures within management database 146, or may be otherwise associated with storage manager 140.

In some cases, the metabase(s) may be included in separate database(s) and/or on separate storage device(s) from primary data 112 and/or secondary copies 116, such that operations related to the metabase do not significantly impact performance on other components in the information management system 100. In other cases, the metabase(s) may be stored along with primary data 112 and/or secondary copies 116. Files or other data objects can be associated with identifiers (e.g., tag entries, etc.) in the media agent 144 (or other indices) to facilitate searches of stored data objects. Among a number of other benefits, the metabase can also allow efficient, automatic identification of files or other data objects to associate with secondary copy or other information management operations (e.g., in lieu of scanning an entire file system). Examples of compatible metabases and data classification operations are provided in U.S. Pat. Nos. 8,229,954 and 7,747,579, which are incorporated by reference herein.

Encryption Operations

The information management system 100 in some cases is configured to process data (e.g., files or other data objects, secondary copies 116, etc.), according to an appropriate encryption algorithm (e.g., Blowfish, Advanced Encryption Standard [AES], Triple Data Encryption Standard [3-DES], etc.) to limit access and provide data security in the information management system 100. The information management system 100 in some cases encrypts the data at the client level, such that the client computing devices 102 (e.g., the data agents 142) encrypt the data prior to forwarding the data to other components, e.g., before sending the data to media agents 144 during a secondary copy operation. In such cases, the client computing device 102 may maintain or have access to an encryption key or passphrase for decrypting the data upon restore. Encryption can also occur when creating copies of secondary copies, e.g., when creating auxiliary copies or archive copies. In yet further embodiments, the secondary storage devices 108 can implement built-in, high performance hardware encryption.

Management and Reporting Operations

Certain embodiments leverage the integrated, ubiquitous nature of the information management system 100 to provide useful system-wide management and reporting functions. Examples of some compatible management and reporting techniques are provided in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.

Operations management can generally include monitoring and managing the health and performance of information management system 100 by, without limitation, performing error tracking, generating granular storage/performance metrics (e.g., job success/failure information, deduplication efficiency, etc.), generating storage modeling and costing information, and the like. As an example, a storage manager 140 or other component in the information management system 100 may analyze traffic patterns and suggest and/or automatically route data via a particular route to minimize congestion. In some embodiments, the system can generate predictions relating to storage operations or storage operation information. Such predictions, which may be based on a trending analysis, may predict various network operations or resource usage, such as network traffic levels, storage media use, use of bandwidth of communication links, use of media agent components, etc. Further examples of traffic analysis, trend analysis, prediction generation, and the like are described in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.

In some configurations, a master storage manager 140 may track the status of storage operation cells in a hierarchy, such as the status of jobs, system components, system resources, and other items, by communicating with storage managers 140 (or other components) in the respective storage operation cells. Moreover, the master storage manager 140 may track the status of its associated storage operation cells and information management operations by receiving periodic status updates from the storage managers 140 (or other components) in the respective cells regarding jobs, system components, system resources, and other items. In some embodiments, a master storage manager 140 may store status information and other information regarding its associated storage operation cells and other system information in its index 150 (or other location).

The master storage manager 140 or other component may also determine whether certain storage-related criteria or other criteria are satisfied, and perform an action or trigger event (e.g., data migration) in response to the criteria being satisfied, such as where a storage threshold is met for a particular volume, or where inadequate protection exists for certain data. For instance, in some embodiments, data from one or more storage operation cells is used to dynamically and automatically mitigate recognized risks, and/or to advise users of risks or suggest actions to mitigate these risks. For example, an information management policy may specify certain requirements (e.g., that a storage device should maintain a certain amount of free space, that secondary copies should occur at a particular interval, that data should be aged and migrated to other storage after a particular period, that data on a secondary volume should always have a certain level of availability and be restorable within a given time period, that data on a secondary volume may be mirrored or otherwise migrated to a specified number of other volumes, etc.). If a risk condition or other criterion is triggered, the system may notify the user of these conditions and may suggest (or automatically implement) an action to mitigate or otherwise address the risk. For example, the system may indicate that data from a primary copy 112 should be migrated to a secondary storage device 108 to free space on the primary storage device 104. Examples of the use of risk factors and other triggering criteria are described in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.

In some embodiments, the system 100 may also determine whether a metric or other indication satisfies particular storage criteria and, if so, perform an action. For example, as previously described, a storage policy or other definition might indicate that a storage manager 140 should initiate a particular action if a storage metric or other indication drops below or otherwise fails to satisfy specified criteria such as a threshold of data protection. Examples of such metrics are described in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.

In some embodiments, risk factors may be quantified into certain measurable service or risk levels for ease of comprehension. For example, certain applications and associated data may be considered to be more important by an enterprise than other data and services. Financial compliance data, for example, may be of greater importance than marketing materials, etc. Network administrators may assign priority values or “weights” to certain data and/or applications, corresponding to the relative importance. The level of compliance of storage operations specified for these applications may also be assigned a certain value. Thus, the health, impact, and overall importance of a service may be determined, such as by measuring the compliance value and calculating the product of the priority value and the compliance value to determine the “service level” and comparing it to certain operational thresholds to determine whether it is acceptable. Further examples of the service level determination are provided in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.

The system 100 may additionally calculate data costing and data availability associated with information management operation cells according to an embodiment of the invention. For instance, data received from the cell may be used in conjunction with hardware-related information and other information about system elements to determine the cost of storage and/or the availability of particular data in the system. Exemplary information generated could include how fast a particular department is using up available storage space, how long data would take to recover over a particular system pathway from a particular secondary storage device, costs over time, etc. Moreover, in some embodiments, such information may be used to determine or predict the overall cost associated with the storage of certain information. The cost associated with hosting a certain application may be based, at least in part, on the type of media on which the data resides, for example. Storage devices may be assigned to a particular cost categories, for example. Further examples of costing techniques are described in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.

Any of the above types of information (e.g., information related to trending, predictions, job, cell or component status, risk, service level, costing, etc.) can generally be provided to users via the user interface 158 in a single, integrated view or console (not shown). The console may support a reporting capability that allows for the generation of a variety of reports, which may be tailored to a particular aspect of information management. Report types may include: scheduling, event management, media management and data aging. Available reports may also include backup history, data aging history, auxiliary copy history, job history, library and drive, media in library, restore history, and storage policy, etc., without limitation. Such reports may be specified and created at a certain point in time as a system analysis, forecasting, or provisioning tool. Integrated reports may also be generated that illustrate storage and performance metrics, risks and storage costing information. Moreover, users may create their own reports based on specific needs.

The integrated user interface 158 can include an option to show a “virtual view” of the system that graphically depicts the various components in the system using appropriate icons. As one example, the user interface 158 may provide a graphical depiction of one or more primary storage devices 104, the secondary storage devices 108, data agents 142 and/or media agents 144, and their relationship to one another in the information management system 100. The operations management functionality can facilitate planning and decision-making. For example, in some embodiments, a user may view the status of some or all jobs as well as the status of each component of the information management system 100. Users may then plan and make decisions based on this data. For instance, a user may view high-level information regarding storage operations for the information management system 100, such as job status, component status, resource status (e.g., communication pathways, etc.), and other information. The user may also drill down or use other means to obtain more detailed information regarding a particular component, job, or the like. Further examples of some reporting techniques and associated interfaces providing an integrated view of an information management system are provided in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.

The information management system 100 can also be configured to perform system-wide e-discovery operations in some embodiments. In general, e-discovery operations provide a unified collection and search capability for data in the system, such as data stored in the secondary storage devices 108 (e.g., backups, archives, or other secondary copies 116). For example, the information management system 100 may construct and maintain a virtual repository for data stored in the information management system 100 that is integrated across source applications 110, different storage device types, etc. According to some embodiments, e-discovery utilizes other techniques described herein, such as data classification and/or content indexing.

Information Management Policies

As indicated previously, an information management policy 148 can include a data structure or other information source that specifies a set of parameters (e.g., criteria and rules) associated with secondary copy and/or other information management operations.

One type of information management policy 148 is a storage policy. According to certain embodiments, a storage policy generally comprises a data structure or other information source that defines (or includes information sufficient to determine) a set of preferences or other criteria for performing information management operations. Storage policies can include one or more of the following items: (1) what data will be associated with the storage policy; (2) a destination to which the data will be stored; (3) datapath information specifying how the data will be communicated to the destination; (4) the type of storage operation to be performed; and (5) retention information specifying how long the data will be retained at the destination (see, e.g., FIG. 1E).

As an illustrative example, data associated with a storage policy can be logically organized into groups. In some cases, these logical groupings can be referred to as “sub-clients”. A sub-client may represent static or dynamic associations of portions of a data volume. Sub-clients may represent mutually exclusive portions. Thus, in certain embodiments, a portion of data may be given a label and the association is stored as a static entity in an index, database or other storage location. Sub-clients may also be used as an effective administrative scheme of organizing data according to data type, department within the enterprise, storage preferences, or the like. Depending on the configuration, sub-clients can correspond to files, folders, virtual machines, databases, etc. In one exemplary scenario, an administrator may find it preferable to separate e-mail data from financial data using two different sub-clients.

A storage policy can define where data is stored by specifying a target or destination storage device (or group of storage devices). For instance, where the secondary storage device 108 includes a group of disk libraries, the storage policy may specify a particular disk library for storing the sub-clients associated with the policy. As another example, where the secondary storage devices 108 include one or more tape libraries, the storage policy may specify a particular tape library for storing the sub-clients associated with the storage policy, and may also specify a drive pool and a tape pool defining a group of tape drives and a group of tapes, respectively, for use in storing the sub-client data. While information in the storage policy can be statically assigned in some cases, some or all of the information in the storage policy can also be dynamically determined based on criteria, which can be set forth in the storage policy. For instance, based on such criteria, a particular destination storage device(s) (or other parameter of the storage policy) may be determined based on characteristics associated with the data involved in a particular storage operation, device availability (e.g., availability of a secondary storage device 108 or a media agent 144), network status and conditions (e.g., identified bottlenecks), user credentials, and the like).

Datapath information can also be included in the storage policy. For instance, the storage policy may specify network pathways and components to utilize when moving the data to the destination storage device(s). In some embodiments, the storage policy specifies one or more media agents 144 for conveying data associated with the storage policy between the source (e.g., one or more host client computing devices 102) and destination (e.g., a particular target secondary storage device 108).

A storage policy can also specify the type(s) of operations associated with the storage policy, such as a backup, archive, snapshot, auxiliary copy, or the like. Retention information can specify how long the data will be kept, depending on organizational needs (e.g., a number of days, months, years, etc.)

Another type of information management policy 148 is a scheduling policy, which specifies when and how often to perform operations. Scheduling parameters may specify with what frequency (e.g., hourly, weekly, daily, event-based, etc.) or under what triggering conditions secondary copy or other information management operations will take place. Scheduling policies in some cases are associated with particular components, such as particular logical groupings of data associated with a storage policy (e.g., a sub-client), client computing device 102, and the like. In one configuration, a separate scheduling policy is maintained for particular logical groupings of data on a client computing device 102. The scheduling policy specifies that those logical groupings are to be moved to secondary storage devices 108 every hour according to storage policies associated with the respective sub-clients.

When adding a new client computing device 102, administrators can manually configure information management policies 148 and/or other settings, e.g., via the user interface 158. However, this can be an involved process resulting in delays, and it may be desirable to begin data protection operations quickly, without awaiting human intervention. Thus, in some embodiments, the information management system 100 automatically applies a default configuration to client computing device 102. As one example, when one or more data agent(s) 142 are installed on one or more client computing devices 102, the installation script may register the client computing device 102 with the storage manager 140, which in turn applies the default configuration to the new client computing device 102. In this manner, data protection operations can begin substantially immediately. The default configuration can include a default storage policy, for example, and can specify any appropriate information sufficient to begin data protection operations. This can include a type of data protection operation, scheduling information, a target secondary storage device 108, data path information (e.g., a particular media agent 144), and the like.

Other types of information management policies 148 are possible, including one or more audit (or security) policies. An audit policy is a set of preferences, rules and/or criteria that protect sensitive data in the information management system 100. For example, an audit policy may define “sensitive objects” as files or objects that contain particular keywords (e.g., “confidential,” or “privileged”) and/or are associated with particular keywords (e.g., in metadata) or particular flags (e.g., in metadata identifying a document or email as personal, confidential, etc.). An audit policy may further specify rules for handling sensitive objects. As an example, an audit policy may require that a reviewer approve the transfer of any sensitive objects to a cloud storage site, and that if approval is denied for a particular sensitive object, the sensitive object should be transferred to a local primary storage device 104 instead. To facilitate this approval, the audit policy may further specify how a secondary storage computing device 106 or other system component should notify a reviewer that a sensitive object is slated for transfer.

Another type of information management policy 148 is a provisioning policy. A provisioning policy can include a set of preferences, priorities, rules, and/or criteria that specify how client computing devices 102 (or groups thereof) may utilize system resources, such as available storage on cloud storage and/or network bandwidth. A provisioning policy specifies, for example, data quotas for particular client computing devices 102 (e.g., a number of gigabytes that can be stored monthly, quarterly or annually). The storage manager 140 or other components may enforce the provisioning policy. For instance, the media agents 144 may enforce the policy when transferring data to secondary storage devices 108. If a client computing device 102 exceeds a quota, a budget for the client computing device 102 (or associated department) is adjusted accordingly or an alert may trigger.

While the above types of information management policies 148 have been described as separate policies, one or more of these can be generally combined into a single information management policy 148. For instance, a storage policy may also include or otherwise be associated with one or more scheduling, audit, or provisioning policies or operational parameters thereof. Moreover, while storage policies are typically associated with moving and storing data, other policies may be associated with other types of information management operations. The following is a non-exhaustive list of items the information management policies 148 may specify:

-   -   schedules or other timing information, e.g., specifying when         and/or how often to perform information management operations;     -   the type of copy 116 (e.g., type of secondary copy) and/or copy         format (e.g., snapshot, backup, archive, HSM, etc.);     -   a location or a class or quality of storage for storing         secondary copies 116 (e.g., one or more particular secondary         storage devices 108);     -   preferences regarding whether and how to encrypt, compress,         deduplicate, or otherwise modify or transform secondary copies         116;     -   which system components and/or network pathways (e.g., preferred         media agents 144) should be used to perform secondary storage         operations;     -   resource allocation among different computing devices or other         system components used in performing information management         operations (e.g., bandwidth allocation, available storage         capacity, etc.);     -   whether and how to synchronize or otherwise distribute files or         other data objects across multiple computing devices or hosted         services; and     -   retention information specifying the length of time primary data         112 and/or secondary copies 116 should be retained, e.g., in a         particular class or tier of storage devices, or within the         information management system 100.

Policies can additionally specify or depend on a variety of historical or current criteria that may be used to determine which rules to apply to a particular data object, system component, or information management operation, such as:

-   -   frequency with which primary data 112 or a secondary copy 116 of         a data object or metadata has been or is predicted to be used,         accessed, or modified;     -   time-related factors (e.g., aging information such as time since         the creation or modification of a data object);     -   deduplication information (e.g., hashes, data blocks,         deduplication block size, deduplication efficiency or other         metrics);     -   an estimated or historic usage or cost associated with different         components (e.g., with secondary storage devices 108);     -   the identity of users, applications 110, client computing         devices 102 and/or other computing devices that created,         accessed, modified, or otherwise utilized primary data 112 or         secondary copies 116;     -   a relative sensitivity (e.g., confidentiality, importance) of a         data object, e.g., as determined by its content and/or metadata;     -   the current or historical storage capacity of various storage         devices;     -   the current or historical network capacity of network pathways         connecting various components within the storage operation cell;     -   access control lists or other security information; and     -   the content of a particular data object (e.g., its textual         content) or of metadata associated with the data object.         Exemplary Storage Policy and Secondary Storage Operations

FIG. 1E includes a data flow diagram depicting performance of storage operations by an embodiment of an information management system 100, according to an exemplary storage policy 148A. The information management system 100 includes a storage manger 140, a client computing device 102 having a file system data agent 142A and an email data agent 142B operating thereon, a primary storage device 104, two media agents 144A, 144B, and two secondary storage devices 108A, 108B: a disk library 108A and a tape library 108B. As shown, the primary storage device 104 includes primary data 112A, which is associated with a logical grouping of data associated with a file system, and primary data 112B, which is associated with a logical grouping of data associated with email. Although for simplicity the logical grouping of data associated with the file system is referred to as a file system sub-client, and the logical grouping of data associated with the email is referred to as an email sub-client, the techniques described with respect to FIG. 1E can be utilized in conjunction with data that is organized in a variety of other manners.

As indicated by the dashed box, the second media agent 144B and the tape library 108B are “off-site”, and may therefore be remotely located from the other components in the information management system 100 (e.g., in a different city, office building, etc.). Indeed, “off-site” may refer to a magnetic tape located in storage, which must be manually retrieved and loaded into a tape drive to be read. In this manner, information stored on the tape library 108B may provide protection in the event of a disaster or other failure.

The file system sub-client and its associated primary data 112A in certain embodiments generally comprise information generated by the file system and/or operating system of the client computing device 102, and can include, for example, file system data (e.g., regular files, file tables, mount points, etc.), operating system data (e.g., registries, event logs, etc.), and the like. The e-mail sub-client, on the other hand, and its associated primary data 112B, include data generated by an e-mail application operating on the client computing device 102, and can include mailbox information, folder information, emails, attachments, associated database information, and the like. As described above, the sub-clients can be logical containers, and the data included in the corresponding primary data 112A, 112B may or may not be stored contiguously.

The exemplary storage policy 148A includes backup copy preferences (or rule set) 160, disaster recovery copy preferences rule set 162, and compliance copy preferences or rule set 164. The backup copy rule set 160 specifies that it is associated with a file system sub-client 166 and an email sub-client 168. Each of these sub-clients 166, 168 are associated with the particular client computing device 102. The backup copy rule set 160 further specifies that the backup operation will be written to the disk library 108A, and designates a particular media agent 144A to convey the data to the disk library 108A. Finally, the backup copy rule set 160 specifies that backup copies created according to the rule set 160 are scheduled to be generated on an hourly basis and to be retained for 30 days. In some other embodiments, scheduling information is not included in the storage policy 148A, and is instead specified by a separate scheduling policy.

The disaster recovery copy rule set 162 is associated with the same two sub-clients 166, 168. However, the disaster recovery copy rule set 162 is associated with the tape library 108B, unlike the backup copy rule set 160. Moreover, the disaster recovery copy rule set 162 specifies that a different media agent, namely 144B, will be used to convey the data to the tape library 108B. As indicated, disaster recovery copies created according to the rule set 162 will be retained for 60 days, and will be generated on a daily basis. Disaster recovery copies generated according to the disaster recovery copy rule set 162 can provide protection in the event of a disaster or other catastrophic data loss that would affect the backup copy 116A maintained on the disk library 108A.

The compliance copy rule set 164 is only associated with the email sub-client 168, and not the file system sub-client 166. Compliance copies generated according to the compliance copy rule set 164 will therefore not include primary data 112A from the file system sub-client 166. For instance, the organization may be under an obligation to store and maintain copies of email data for a particular period of time (e.g., 10 years) to comply with state or federal regulations, while similar regulations do not apply to the file system data. The compliance copy rule set 164 is associated with the same tape library 108B and media agent 144B as the disaster recovery copy rule set 162, although a different storage device or media agent could be used in other embodiments. Finally, the compliance copy rule set 164 specifies that copies generated under the compliance copy rule set 164 will be retained for 10 years, and will be generated on a quarterly basis.

At step 1, the storage manager 140 initiates a backup operation according to the backup copy rule set 160. For instance, a scheduling service running on the storage manager 140 accesses scheduling information from the backup copy rule set 160 or a separate scheduling policy associated with the client computing device 102, and initiates a backup copy operation on an hourly basis. Thus, at the scheduled time slot the storage manager 140 sends instructions to the client computing device 102 (i.e., to both data agent 142A and data agent 142B) to begin the backup operation.

At step 2, the file system data agent 142A and the email data agent 142B operating on the client computing device 102 respond to the instructions received from the storage manager 140 by accessing and processing the primary data 112A, 112B involved in the copy operation, which can be found in primary storage device 104. Because the operation is a backup copy operation, the data agent(s) 142A, 142B may format the data into a backup format or otherwise process the data.

At step 3, the client computing device 102 communicates the retrieved, processed data to the first media agent 144A, as directed by the storage manager 140, according to the backup copy rule set 160. In some other embodiments, the information management system 100 may implement a load-balancing, availability-based, or other appropriate algorithm to select from the available set of media agents 144A, 144B. Regardless of the manner the media agent 144A is selected, the storage manager 140 may further keep a record in the storage manager database 146 of the association between the selected media agent 144A and the client computing device 102 and/or between the selected media agent 144A and the backup copy 116A.

The target media agent 144A receives the data from the client computing device 102, and at step 4 conveys the data to the disk library 108A to create the backup copy 116A, again at the direction of the storage manager 140 and according to the backup copy rule set 160. The secondary storage device 108A can be selected in other ways. For instance, the media agent 144A may have a dedicated association with a particular secondary storage device(s), or the storage manager 140 or media agent 144A may select from a plurality of secondary storage devices, e.g., according to availability, using one of the techniques described in U.S. Pat. No. 7,246,207, which is incorporated by reference herein.

The media agent 144A can also update its index 153 to include data and/or metadata related to the backup copy 116A, such as information indicating where the backup copy 116A resides on the disk library 108A, data and metadata for cache retrieval, etc. The storage manager 140 may similarly update its index 150 to include information relating to the storage operation, such as information relating to the type of storage operation, a physical location associated with one or more copies created by the storage operation, the time the storage operation was performed, status information relating to the storage operation, the components involved in the storage operation, and the like. In some cases, the storage manager 140 may update its index 150 to include some or all of the information stored in the index 153 of the media agent 144A. After the 30 day retention period expires, the storage manager 140 instructs the media agent 144A to delete the backup copy 116A from the disk library 108A. Indexes 150 and/or 153 are updated accordingly.

At step 5, the storage manager 140 initiates the creation of a disaster recovery copy 116B according to the disaster recovery copy rule set 162.

At step 6, illustratively based on the instructions received from the storage manager 140 at step 5, the specified media agent 144B retrieves the most recent backup copy 116A from the disk library 108A.

At step 7, again at the direction of the storage manager 140 and as specified in the disaster recovery copy rule set 162, the media agent 144B uses the retrieved data to create a disaster recovery copy 116B on the tape library 108B. In some cases, the disaster recovery copy 116B is a direct, mirror copy of the backup copy 116A, and remains in the backup format. In other embodiments, the disaster recovery copy 116B may be generated in some other manner, such as by using the primary data 112A, 112B from the primary storage device 104 as source data. The disaster recovery copy operation is initiated once a day and the disaster recovery copies 116B are deleted after 60 days; indexes are updated accordingly when/after each information management operation is executed/completed.

At step 8, the storage manager 140 initiates the creation of a compliance copy 116C, according to the compliance copy rule set 164. For instance, the storage manager 140 instructs the media agent 144B to create the compliance copy 116C on the tape library 108B at step 9, as specified in the compliance copy rule set 164. In the example, the compliance copy 116C is generated using the disaster recovery copy 116B. In other embodiments, the compliance copy 116C is instead generated using either the primary data 112B corresponding to the email sub-client or using the backup copy 116A from the disk library 108A as source data. As specified, in the illustrated example, compliance copies 116C are created quarterly, and are deleted after ten years, and indexes are kept up-to-date accordingly.

While not shown in FIG. 1E, at some later point in time, a restore operation can be initiated involving one or more of the secondary copies 116A, 1168, 116C. As one example, a user may manually initiate a restore of the backup copy 116A by interacting with the user interface 158 of the storage manager 140. The storage manager 140 then accesses data in its index 150 (and/or the respective storage policy 148A) associated with the selected backup copy 116A to identify the appropriate media agent 144A and/or secondary storage device 108A.

In other cases, a media agent may be selected for use in the restore operation based on a load balancing algorithm, an availability based algorithm, or other criteria. The selected media agent 144A retrieves the data from the disk library 108A. For instance, the media agent 144A may access its index 153 to identify a location of the backup copy 116A on the disk library 108A, or may access location information residing on the disk 108A itself.

When the backup copy 116A was recently created or accessed, the media agent 144A accesses a cached version of the backup copy 116A residing in the index 153, without having to access the disk library 108A for some or all of the data. Once it has retrieved the backup copy 116A, the media agent 144A communicates the data to the source client computing device 102. Upon receipt, the file system data agent 142A and the email data agent 142B may unpackage (e.g., restore from a backup format to the native application format) the data in the backup copy 116A and restore the unpackaged data to the primary storage device 104.

Exemplary Applications of Storage Policies

The storage manager 140 may permit a user to specify aspects of the storage policy 148A. For example, the storage policy can be modified to include information governance policies to define how data should be managed in order to comply with a certain regulation or business objective. The various policies may be stored, for example, in the management database 146. An information governance policy may comprise a classification policy, which is described herein. An information governance policy may align with one or more compliance tasks that are imposed by regulations or business requirements. Examples of information governance policies might include a Sarbanes-Oxley policy, a HIPAA policy, an electronic discovery (E-Discovery) policy, and so on.

Information governance policies allow administrators to obtain different perspectives on all of an organization's online and offline data, without the need for a dedicated data silo created solely for each different viewpoint. As described previously, the data storage systems herein build a centralized index that reflects the contents of a distributed data set that spans numerous clients and storage devices, including both primary and secondary copies, and online and offline copies. An organization may apply multiple information governance policies in a top-down manner over that unified data set and indexing schema in order to permit an organization to view and manipulate the single data set through different lenses, each of which is adapted to a particular compliance or business goal. Thus, for example, by applying an E-discovery policy and a Sarbanes-Oxley policy, two different groups of users in an organization can conduct two very different analyses of the same underlying physical set of data copies, which may be distributed throughout the organization and information management system.

A classification policy defines a taxonomy of classification terms or tags relevant to a compliance task and/or business objective. A classification policy may also associate a defined tag with a classification rule. A classification rule defines a particular combination of criteria, such as users who have created, accessed or modified a document or data object; file or application types; content or metadata keywords; clients or storage locations; dates of data creation and/or access; review status or other status within a workflow (e.g., reviewed or un-reviewed); modification times or types of modifications; and/or any other data attributes in any combination, without limitation. A classification rule may also be defined using other classification tags in the taxonomy. The various criteria used to define a classification rule may be combined in any suitable fashion, for example, via Boolean operators, to define a complex classification rule. As an example, an E-discovery classification policy might define a classification tag “privileged” that is associated with documents or data objects that (1) were created or modified by legal department staff, or (2) were sent to or received from outside counsel via email, or (3) contain one of the following keywords: “privileged” or “attorney” or “counsel”, or other like terms.

One specific type of classification tag, which may be added to an index at the time of indexing, is an entity tag. An entity tag may be, for example, any content that matches a defined data mask format. Examples of entity tags might include, e.g., social security numbers (e.g., any numerical content matching the formatting mask XXX-XX-XXXX), credit card numbers (e.g., content having a 13-16 digit string of numbers), SKU numbers, product numbers, etc.

A user may define a classification policy by indicating criteria, parameters or descriptors of the policy via a graphical user interface, such as a form or page with fields to be filled in, pull-down menus or entries allowing one or more of several options to be selected, buttons, sliders, hypertext links or other known user interface tools for receiving user input, etc. For example, a user may define certain entity tags, such as a particular product number or project ID code that is relevant in the organization. In some implementations, the classification policy can be implemented using cloud-based techniques. For example, the storage devices may be cloud storage devices, and the storage manager 140 may execute cloud service provider API over a network to classify data stored on cloud storage devices.

Exemplary Secondary Copy Formatting

The formatting and structure of secondary copies 116 can vary, depending on the embodiment. In some cases, secondary copies 116 are formatted as a series of logical data units or “chunks” (e.g., 512 MB, 1 GB, 2 GB, 4 GB, or 8 GB chunks). This can facilitate efficient communication and writing to secondary storage devices 108, e.g., according to resource availability. For example, a single secondary copy 116 may be written on a chunk-by-chunk basis to a single secondary storage device 108 or across multiple secondary storage devices 108. In some cases, users can select different chunk sizes, e.g., to improve throughput to tape storage devices.

Generally, each chunk can include a header and a payload. The payload can include files (or other data units) or subsets thereof included in the chunk, whereas the chunk header generally includes metadata relating to the chunk, some or all of which may be derived from the payload. For example, during a secondary copy operation, the media agent 144, storage manager 140, or other component may divide the associated files into chunks and generate headers for each chunk by processing the constituent files. The headers can include a variety of information such as file identifier(s), volume(s), offset(s), or other information associated with the payload data items, a chunk sequence number, etc. Importantly, in addition to being stored with the secondary copy 116 on the secondary storage device 108, the chunk headers can also be stored to the index 153 of the associated media agent(s) 144 and/or the index 150. This is useful in some cases for providing faster processing of secondary copies 116 during restores or other operations. In some cases, once a chunk is successfully transferred to a secondary storage device 108, the secondary storage device 108 returns an indication of receipt, e.g., to the media agent 144 and/or storage manager 140, which may update their respective indexes 153, 150 accordingly. During restore, chunks may be processed (e.g., by the media agent 144) according to the information in the chunk header to reassemble the files.

Data can also be communicated within the information management system 100 in data channels that connect the client computing devices 102 to the secondary storage devices 108. These data channels can be referred to as “data streams”, and multiple data streams can be employed to parallelize an information management operation, improving data transfer rate, among providing other advantages. Example data formatting techniques including techniques involving data streaming, chunking, and the use of other data structures in creating copies (e.g., secondary copies) are described in U.S. Pat. Nos. 7,315,923 and 8,156,086, and 8,578,120, each of which is incorporated by reference herein.

FIGS. 1F and 1G are diagrams of example data streams 170 and 171, respectively, which may be employed for performing data storage operations. Referring to FIG. 1F, the data agent 142 forms the data stream 170 from the data associated with a client computing device 102 (e.g., primary data 112). The data stream 170 is composed of multiple pairs of stream header 172 and stream data (or stream payload) 174. The data streams 170 and 171 shown in the illustrated example are for a single-instanced storage operation, and a stream payload 174 therefore may include both single-instance (“SI”) data and/or non-SI data. A stream header 172 includes metadata about the stream payload 174. This metadata may include, for example, a length of the stream payload 174, an indication of whether the stream payload 174 is encrypted, an indication of whether the stream payload 174 is compressed, an archive file identifier (ID), an indication of whether the stream payload 174 is single instanceable, and an indication of whether the stream payload 174 is a start of a block of data.

Referring to FIG. 1G, the data stream 171 has the stream header 172 and stream payload 174 aligned into multiple data blocks. In this example, the data blocks are of size 64 KB. The first two stream header 172 and stream payload 174 pairs comprise a first data block of size 64 KB. The first stream header 172 indicates that the length of the succeeding stream payload 174 is 63 KB and that it is the start of a data block. The next stream header 172 indicates that the succeeding stream payload 174 has a length of 1 KB and that it is not the start of a new data block. Immediately following stream payload 174 is a pair comprising an identifier header 176 and identifier data 178. The identifier header 176 includes an indication that the succeeding identifier data 178 includes the identifier for the immediately previous data block. The identifier data 178 includes the identifier that the data agent 142 generated for the data block. The data stream 171 also includes other stream header 172 and stream payload 174 pairs, which may be for SI data and/or for non-SI data.

FIG. 1H is a diagram illustrating the data structures 180 that may be used to store blocks of SI data and non-SI data on the storage device (e.g., secondary storage device 108). According to certain embodiments, the data structures 180 do not form part of a native file system of the storage device. The data structures 180 include one or more volume folders 182, one or more chunk folders 184/185 within the volume folder 182, and multiple files within the chunk folder 184. Each chunk folder 184/185 includes a metadata file 186/187, a metadata index file 188/189, one or more container files 190/191/193, and a container index file 192/194. The metadata file 186/187 stores non-SI data blocks as well as links to SI data blocks stored in container files. The metadata index file 188/189 stores an index to the data in the metadata file 186/187. The container files 190/191/193 store SI data blocks. The container index file 192/194 stores an index to the container files 190/191/193. Among other things, the container index file 192/194 stores an indication of whether a corresponding block in a container file 190/191/193 is referred to by a link in a metadata file 186/187. For example, data block B2 in the container file 190 is referred to by a link in the metadata file 187 in the chunk folder 185. Accordingly, the corresponding index entry in the container index file 192 indicates that the data block B2 in the container file 190 is referred to. As another example, data block B1 in the container file 191 is referred to by a link in the metadata file 187, and so the corresponding index entry in the container index file 192 indicates that this data block is referred to.

As an example, the data structures 180 illustrated in FIG. 1H may have been created as a result of two storage operations involving two client computing devices 102. For example, a first storage operation on a first client computing device 102 could result in the creation of the first chunk folder 184, and a second storage operation on a second client computing device 102 could result in the creation of the second chunk folder 185. The container files 190/191 in the first chunk folder 184 would contain the blocks of SI data of the first client computing device 102. If the two client computing devices 102 have substantially similar data, the second storage operation on the data of the second client computing device 102 would result in the media agent 144 storing primarily links to the data blocks of the first client computing device 102 that are already stored in the container files 190/191. Accordingly, while a first storage operation may result in storing nearly all of the data subject to the storage operation, subsequent storage operations involving similar data may result in substantial data storage space savings, because links to already stored data blocks can be stored instead of additional instances of data blocks.

If the operating system of the secondary storage computing device 106 on which the media agent 144 operates supports sparse files, then when the media agent 144 creates container files 190/191/193, it can create them as sparse files. A sparse file is type of file that may include empty space (e.g., a sparse file may have real data within it, such as at the beginning of the file and/or at the end of the file, but may also have empty space in it that is not storing actual data, such as a contiguous range of bytes all having a value of zero). Having the container files 190/191/193 be sparse files allows the media agent 144 to free up space in the container files 190/191/193 when blocks of data in the container files 190/191/193 no longer need to be stored on the storage devices. In some examples, the media agent 144 creates a new container file 190/191/193 when a container file 190/191/193 either includes 100 blocks of data or when the size of the container file 190 exceeds 50 MB. In other examples, the media agent 144 creates a new container file 190/191/193 when a container file 190/191/193 satisfies other criteria (e.g., it contains from approximately 100 to approximately 1000 blocks or when its size exceeds approximately 50 MB to 1 GB).

In some cases, a file on which a storage operation is performed may comprise a large number of data blocks. For example, a 100 MB file may comprise 400 data blocks of size 256 KB. If such a file is to be stored, its data blocks may span more than one container file, or even more than one chunk folder. As another example, a database file of 20 GB may comprise over 40,000 data blocks of size 512 KB. If such a database file is to be stored, its data blocks will likely span multiple container files, multiple chunk folders, and potentially multiple volume folders. Restoring such files may require accessing multiple container files, chunk folders, and/or volume folders to obtain the requisite data blocks.

Value Calculation Systems

Many organizations are hampered by problems associated with data protection, application recovery, and data management. Users from small businesses to large enterprises are grappling with data growth, struggling to make data accessible, and fighting to reduce risk, cost, and the complexity of their IT operations. The disclosed system teaches a user how it may reduce complexity and improve efficiency by implementing an integrated data management and protection solution, such as the information management system described above. Indeed, the system identifies the value received by the user in a data protection and data management solution that integrates multiple data protection and data management functions. The integrated system can combine archiving, backup, snapshot management, reporting, secure data access, eDiscovery and data analytics, among other functions, thus simplifying data protection and data management for an organization.

Traditional total cost of ownership or return on investment (TCO/ROI) analyses tend to focus on hardware and software infrastructure costs, and labor or administrative effects. The disclosed system expands the conversation to discuss other value received by a user, identified across three categories that are more broad than finances in both scope and impact. These categories are simplification and efficiency, risk reduction, and unlocking data value.

The disclosed system identifies value in an integrated data management and protection solution, like the information management system described above, by analyzing information associated with a user's data management and protection needs. The system identifies efficiencies for the user that would result from implementing an integrated system, identifying value in reducing complexity and infrastructure costs, improving data protection and recovery performance, and boosting IT operational efficiencies. The system also identifies value in risk reduced as a result of reducing operational complexity, improving recovery efficiency, and minimizing relative exposure to legal issues, compliance failures, downtime, and data loss. Moreover, an integrated system can make data easily searchable and accessible. The system can help illustrate the value that data managed by an integrated system can create for a business, for example, by improving employee productivity, enhancing organizational decision-making, and enabling IT to devote resources to more strategic activities.

To convey identified value, the system generates a value dashboard, exhibiting data and graphics portraying the benefits to a user of utilizing an integrated data management and protection system. The value dashboard is created using information related to a user's data management and protection needs. This includes data describing the user's current data management and protection system, information describing the user's business or its industry, input from a user to a questionnaire, and the like. The system applies value functions to the received information, resulting in value data, which is presented to the user in the value dashboard.

FIG. 2 is a block diagram of various modules of a suitable system 200 for identifying value in data management and protection systems and conveying that value to a user. The system 200 generates a value dashboard, which displays value that would be or is received by a customer or user implementing an integrated data management and protection system. The system 200 includes a value computation module 210 and a user interface module 220. The system receives user input and outputs an input interface and a value dashboard. The system 200 accesses and stores data in value functions data storage 270, solutions data storage 275, and interface data storage 280.

The system can receive user input in a variety of ways. User input can be solicited and received via a webpage or an application. The system can generate and output a graphical input interface that is displayed to a user for entering data. An input interface can include a questionnaire for soliciting feedback from the user and/or fields for receiving a user's submission of information related to a user's data management and protection needs, including data about a current system used by the user, information about the user's business, information about the industry that the user belongs to, information describing data management and protection needs of similarly situated users, and the like. FIGS. 4A-4J show example input interfaces. In some implementations, the system receives a file that contains user input. In some implementations, the system generates vignettes or displays, which are included as part of a value story. These displays tell a value story but also receives input from a user. A user can interact with such displays by adjusting slider buttons, submitting information into an entry field, or the like. An example of such displays is discussed with reference to FIGS. 6A through 9E.

The system generates a value dashboard, which displays value that a user would receive by adopting an integrated data management and protection system. FIGS. 5A and 5B show representative value dashboards. Value is displayed through statistics, lists of features, graphs, and so forth. Value is represented with regard to value categories, including simplification, risk reduction, and data value. Value thus extends well beyond just the monetary cost to a user, and thus the present system is able to provide a richer definition of “value” to a user. As discussed below, the system can display a value story on a dashboard.

The value computation module 210 identifies value in an integrated data management and protection system for a user. The value computation module 210 accesses value functions in value functions data storage 270, and applies the value functions to user input, resulting in value data, as described below. Value functions include rules and algorithms for identifying or quantifying value. For example, a value function may include an equation that when applied to user input, results in a time efficiency realized by implementing an integrated system (often shown in the Figures as compared to a system provided by Commvault, Inc.). In some implementations, a value function is used to compute a data and information risk exposure score. A value function can be determined based on empirically collected data. For example, a value function can be formed by creating an equation that meets data observed from other users implementing an integrated data management and protection system. Value functions can also generate value data for alternative data management and protection systems. For example, the value computation module 210 can apply value metrics to information about a user's existing data management and protection system.

Some value functions leverage user data to generate formulas that can take an input, such as amount of data in a user's environment, and estimate annual administrative hours saved or annual full time employee hires avoided. The estimated hours saved and hires avoided values may be developed empirically from analyzing existing data.

Other formulas are more complex. For example, a Data and Information Risk Exposure Index (DIRE Index, described herein) weights and scores multiple different factors and aggregates the scores on a single 10-point scale, and compares the DIRE Index scores of current or competitive capabilities to the capabilities of an integrated system. The DIRE Index can aggregate operational complexity, recovery efficiency and data protection efficiency, as well as relative exposure to legal issues, compliance failures, downtime or data loss. The system can score these elements of risk and then combine them on a color-coded 10-point scale to give users a quick idea of risk exposure.

In some implementations, the value computation module 210 identifies value in an integrated system for a user based solely on user input. However, sometimes a person, with little user information, wishes to view or depict value associated with the user implementing an integrated system. For example, a person knowing little about an organization may wish to develop a value story showing value received from an integrated system for presenting to the organization. The value computation module 210 can identify in solutions data storage 275 information associated with a data management and protection system implemented by another user. The value computation module may receive a user's selection of an existing system, or the value computation module may identify a solution or information about a previous user based at least in part on available input from the user. The value computation module 210 can generate value data based at least in part on this retrieved information.

The user interface module 220 generates input interfaces and value dashboards, which are output to the user. The user interface module formats input interfaces and value dashboards based on interface data accessed in interface data storage 280. In some implementations, the user interface module 220 correlates value functions with entry fields of an input interface, enabling the value computation module to easily identify appropriate value functions.

The system 200 identifies value with respect to at least three value categories: simplification, risk reduction, and unlocking data value. Simplification includes value associated with IT efficiencies (e.g., reducing a number of products across an IT environment), operation efficiencies (e.g., reducing operational time), storage efficiencies (e.g., reducing amount of data that is transmitted over the network and stored across storage silos), and administrative efficiencies (e.g., reduction in manual administrative hours and number of full time employees needing to be hired). Risk reduction includes value associated with complexity downtime and expected risk, data protection (e.g., reliability of data protection operations and operation time), recovery (e.g., a number of recovery point objections, and a reduction in restore time for critical applications), operations (e.g., encryption coverage, reporting coverage, chance of fail compliance, or audit), and operations (encryption coverage, reporting coverage, chance of fail compliance, or audit). Furthermore, the system can calculate a data and information risk exposure score by aggregating the risk reduction category and subcategories, which are weighted and scaled to 10-points.

Example Processes

FIG. 3 is a flow diagram of a process 300 implemented by the value calculation system 200 for identifying value in an integrated data management and protection system and automatically conveying this value. In some implementations, the system generates vignettes or displays, which include value discussions for presentation.

At a block 305, the system maintains value functions for determining value associated with an integrated data management and protection system. The system may maintain a separate value function for each of the three value categories: simplification, risk reduction, and unlocking data value, and may even maintain separate value functions for each subcategories noted herein for the three categories. The system can also maintain value functions for determining value associated with alternative data management and protection systems. For example, value functions may identify value in a competitor's data management and protection system, a generic system, or a system currently being implemented by the user. Alternative systems may combine services offered by different providers of data management and protection. In some implementations, the system compares identified value associated with an integrated data management and protection system with identified value associated with an alternative data management and protection system.

At a block 310, the system generates an input interface. The input interface is a graphical user interface that is displayed to a user to solicit and receive feedback about a user's data management and protection needs. The input interface includes data entry fields, including drop down menus, text input fields, and the like, through which a user may provide input. The input interface also displays graphics that the user can select or otherwise interact with in order to provide input. In some implementations, a value function is associated with one or more data entry fields, and a result of the value function is computed based on information entered in the one or more data entry fields. FIGS. 4A-J show a representative input interface, which includes multiple interfaces for soliciting and receiving input from a user.

At a block 315, the system receives user input related to a user's data management and protection. User input is received via the data entry fields of the input interface. User input may describe a current data management and protection system that the user is using. It may describe data management or protection features that the user wishes to use. User input also includes a selection by a user of an integrated system employed by another user, or a selection of a profile of a user that is similarly situated (e.g., similar size, industry, data management needs, etc.). For example, a person for a provider of data management and protection system, wishing to present the value associated with her product to a medium-sized law firm, may select a user profile of a medium-sized law firm. In some implementations, user input includes information about a user's business operations, including a number of people employed by the user, an industry that the user belongs to, information about its business model, and so forth. In some implementations, rather than receive user input via the input interface, the system receives a data file containing information comparable to user input.

The input interface of FIGS. 4A-J includes data entry fields, including text fields, drop down menus, check boxes, and other entry mechanisms. Data entry fields can be prepopulated with values based on a default configuration or prior user input. A user can traverse the interfaces of FIG. 4A-J using buttons “Previous” and “Next.” A user can progress through the interfaces without submitting information with regard to some entry fields.

FIG. 4A shows an interface that includes an index, which outlines steps to be taken by the user for submitting information related to data management and data storage for a user. FIG. 4B shows an interface for receiving the submission of information related to an account, including information about the user, including contact information, account information, and financial information. FIG. 4B also includes an entry field of scenario, through which a user can specify a name for saving the data submitted via the input interface. FIG. 4C shows an interface for receiving a submission by a user of objectives for the user. Objectives are organized under the three value categories: simplification, risk reduction, and data value. The interface can receive as input a numerical score ranking (e.g. within a range of 1-5) a user's top objectives by entry of a number in an entry field adjacent to a listed objective, such as in the entry field by the objective “Archive—Email.” The interface may receive a selection of a checkbox associated with an objective. FIG. 4D shows an interface for receiving a submission by a user of functionality that the user wishes from an integrated data management and protection system. A user may make a selection of a listed functionality by selecting a checkbox associated therewith.

FIG. 4E shows an interface for receiving a submission of information associated with a data management and protection environment for the user. A user can submit information related to an alternative implementation and an integrated system. FIG. 4F shows an interface for receiving a submission of information associated with spending for an alternative data management and protection system. The user may supply data related to the annual software, hardware, and services and disaster recovery costs of using an alternative system. FIG. 4G shows an interface for receiving a submission of information associated with spending for an integrated data management and protection system. The user may supply data related to the annual software, hardware, and services and disaster recovery costs of using an integrated system.

FIGS. 4H-4J show interfaces for soliciting information related to value categories. FIG. 4H shows an interface for receiving information related to simplification, including information describing the alternative system for the user and information about a configuration for the integrated system for the user. The system automatically populates some entry fields with computed values as information related to the alternative system is submitted (as shown in the example of FIG. 4H). FIG. 4I shows an interface for receiving information related to risk reduction, including information describing the alternative system and information describing the configuration of the integrated system for the user (as shown in the example of FIG. 4I). The system automatically populates some entry fields. FIG. 4J shows an interface for receiving information related to unlocking the value of the value to the user of unlocking the stored data.

Returning to FIG. 3, after receiving user input, the process 300 proceeds to a decision block 320, and the system 200 determines whether user input was satisfactory for identifying value in an integrated system for the user. In some implementations, the system determines that user input was not satisfactory when the user has submitted a value in an entry field that is determined to be submitted in error, such as if the value exceeds a predetermined threshold. In some implementations, the system determines that user input was not satisfactory if the user has not submitted information into a mandatory entry field. In some implementations, the system determines that user input is satisfactory if it includes any information. If the system determines that the user input is not satisfactory, the process proceeds to a block 325, and the system generates a request that the user submit further information. In some implementations, the system displays an input interface for soliciting needed information. The process then returns to block 310.

If at decision block 320 the system 200 determines that user input is satisfactory, the process proceeds to a block 330, and the system identifies value functions to apply to the user input to identify value in an integrated data management and protection system. In some implementations, the system identifies a default set of value functions used to produce a dashboard. In some implementations, the system accesses a data structure that correlates received input and value functions, enabling the system to identify value functions that should be applied to received input based on the input that was received. In some implementations, a value function is associated with one or more entry fields of an input interface, and are thus identified based on their association.

At a block 335, the system applies the identified value functions to the user input, generating value data. Value data is discussed further below with reference to FIGS. 5A and 5B. In some implementations, value data includes a data and information risk exposure score (DIRE Index) generated by the system 200. For example, a data and information risk exposure score may be generated by aggregating weighted scores associated with operational complexity, recovery efficiency, and relative exposure to legal issues, compliance failures, downtime or data loss, and normalizing the score on a 10-point scale. For example, operational complexity may be represented by a ranking on a scale of 1-100; recovery efficiency may be represented by a percentage; and relative exposure to legal issues, compliance failures, downtime or data loss may be represented by a ranking on a scale of 1-5. The system can determine values for each of these metrics based on user input and compute a data and information risk exposure score. For instance, the system may insert values for operational complexity, recovery efficiency, and relative exposure to legal issues, compliance failures, downtime or data loss, in a function for calculating a data and information risk score. As a simple example, a function for calculating a data and information risk score may divide an operational complexity rank by 10, divide a recovery efficiency percentage by 10, and multiply a relative exposure score by 2, and add these values together to arrive at a data and information risk exposure score. A more detailed algorithm is discussed below.

The DIRE Index represents a risk score for an information backup/recovery system. It is typically calculated as a comparison between two information backup systems (with one of those two systems shown in the Figures as the Commvault system). Two risk scores can be compared to determine which system is more or less prone to risk. The Index is based on an accumulated score of individual metric scores, where each metric is a measurable attribute of the system's environment that represents an element of risk to the data such as the number of backups per day or the amount of time it takes to perform a backup.

Multiple, different metrics (e.g. 20 metrics) are measured in different categories (e.g. four categories). Each individual metric value is run through a function that results in a score between, e.g. the best possible score of 0.0 and the worst possible score of 10.0. Each metric score is multiplied by a normalized weight to produce its weighted score. All weighted scores are then summed to determine the overall score for an environment where a risk score of 0.0 is minimum risk and a risk score of 10.0 is maximum risk. The score is the same as the Index.

A normalized weight is determined by dividing the weight by the sum of all weights where each metric has one weight representing its relative importance in determining the overall Index value or score. Using this technique to derive the normalized weight allows the actual weights entered to be any value. The user entering the weights may not be cognizant of the value of each weight relative to all other weights—other than that any range of values for the weights can be used. User data informs the value of each weight relative to all other weights. For example: IT Complexity and Annual Unplanned Downtime are weighted, under an example algorithm, higher than Incremental Backup Time or Subjective Level of Risk, which means that IT Complexity and Annual Downtime are more meaningful when assessing data and information's risk to a business.

Each metric is normalized to a risk score between 0.0 and 10.0 using a semi-complex straight line curve with three different slopes and four points that define the curve. See example in FIG. 10. The theory behind the curve is to place additional emphasis or less emphasis on certain metric values depending on where they fall relative to four metric value points:

-   -   1) The metric value that represents the lowest or best possible         risk score of 0.0.     -   2) The metric value expected with a particular integrated system         and which results in the risk score of 2.0.     -   3) The metric value expected with another system and which         results in the risk score of 7.0.     -   4) The metric value that represents the highest or worst         possible risk score of 10.0.         An example of the curve is shown in FIG. 10 for the metric         Incremental Backup Time (in minutes). In this example, less time         to perform the backup represents less risk and vice versa. The         four metric value points are, e.g. 120 (0.0 risk score), 170         (2.0 risk score), 320 (7.0 risk score), and 500 (10.0 risk         score).

The semi-complex straight line curve resulting from these four points represents the function used to determine the risk score for any metric value between the lowest possible value and the highest possible value for each specific metric. A process for implementing such risk calculation is as follows.

Step 1—Bring the metric value within a valid range. If less than the minimum then set to the minimum. If greater than the maximum then set to the maximum.

Step 2—Using the line segment from the curve of FIG. 10 on which the metric value falls, use straight line interpolation to determine the resulting risk score. Given a metric value and two end points (high and low) each consisting of a value/score pair, a risk score is calculated using, e.g. the formula: Score=(HighScore−LowScore)/(HighValue−LowValue)*(Value−LowValue)+LowScore

Note that if the metric's best value was greater than the worst value then the line would slope downward from left to right.

More complete logic representing this calculation, using pseudocode, is as follows. In this code the term “Best” represents the best possible value resulting in the best possible score of 0.0 and “Worst” represents the worst possible value resulting in the worst possible score. The values BestValue, CVValue, OtherValue, and WorstValue are passed in as parameters.

BestScore = 0 CVScore = 2 OtherScore = 7 WorstScore = 10 If BestValue < WorstValue Then  Value = Minimum of (Maximum of (Value, BestValue), WorstValue) Else  Value = Minimum of (Maximum of (Value, WorstValue), BestValue) If Value is Between BestValue and CVValue Inclusive Then  Score = (CVScore − BestScore) / (CVValue − BestValue) * (Value   − BestValue) + BestScore If Value is Between CVValue and OtherValue Inclusive Then  Score = (OtherScore − CVScore) / (OtherValue − CVValue) *   (Value − CVValue) + CVScore If Value is Between OtherValue and WorstValue Inclusive Then  Score = (WorstScore − OtherScore) / (WorstValue − OtherValue)   * (Value − OtherValue) + OtherScore

With all of the metric risk scores determined, the Index score is determined by multiplying each metric risk score by the normalized weight. Each normalized weight is calculated by dividing the weight entered by the analyst by the sum of all weights entered user. Below are examples of metrics to be used to determine the Index score. With each is also listed the weight, the best or least risky value (Best), the expected new system value (CV), the expected existing system value (Other), and the worst or most risky value (Worst).

Category Metric Weight Best CV Other Worst Complexity, Downtime, Subjective Risk IT Complexity 12 2 4 8 24 Complexity, Downtime, Subjective Risk Annual Unplanned Downtime Hours 10 0 11 25 48 Complexity, Downtime, Subjective Risk Subjective Weighted Level of Risk 2 1 2 4 5 Data Protection Backup Reliability 8 100% 94% 79% 60% Data Protection Restore Reliability 8 100% 96% 75% 60% Data Protection Full Backup Time Minutes 4 120 960 1660 2000 Data Protection Incremental Backup Time Minutes 2 120 170 320 500 Data Protection Offsite Copy Time Minutes 2 120 170 320 500 Recovery Number of Recovery Points per Day 5 12 6 1 1 Recovery Exchange Restore Time Minutes 3 10 50 570 700 Recovery Oracle Restore Time Minutes 3 50 130 330 400 Recovery SQL Restore Time Minutes 3 30 60 250 400 Recovery VM Restore Time Minutes 3 50 85 260 400 Recovery RPO (Recovery Point Objective) 4 50 240 690 900 Minutes Operations Chance to Fail Compliance 4  0%  2% 10% 15% Operations Chance to Fail Audit 4  0%  2% 10% 15% Operations Chance of Theft or Breach 9  0%  2% 10% 15% Operations Protection Coverage 8 100% 98% 85% 40% Operations Encryption Coverage 4 100% 98% 50% 40% Operations Reporting Coverage 2 100% 98% 65% 40%

An example algorithm or formula for generating the Index value or score may be:

-   -   1. Receive as input numerous numeric inputs for each of numerous         factors (e.g. ˜20 values)     -   2. Weight each value     -   3. Assign a score for each weighted value based on bounded         values     -   4. Add the scores and normalize to 10-point scale

At block 340, the system generates a value dashboard using the generated value data and Index score. The value dashboard displays value data, including raw data, computed values, charts, and so forth, for conveying value to the user. FIGS. 5A and 5B show a representative value dashboard 500. FIG. 5A shows value data related to the financial value category. The dashboard displays financial data comparing an alternative or existing data management and protection system and an integrated data management and protection system, including return on investment (ROI) time horizon (e.g. 2 years), ROI, payback period, internal rate of return (IRR), net present value (NPV), net benefit. The dashboard also displays a line graph showing cumulative spending for an integrated system versus an alternative system; a bar graph showing total spending related to software, hardware, services, and labor; and a bar graph showing the net benefit of software, hardware, services, and labor costs between the integrated system and the alternative system.

FIG. 5B shows value data related to value categories of simplification, risk reduction, and unlocking of data value. The dashboard displays line and bar graphs to convey value associated with simplification. A first bar/line graph 510 compares an alternative/existing system and an integrated system, showing storage efficiencies and terabytes (TB) transferred, including an amount of data (in TB) backed up per week and an amount of protection data (in TB) sent over the network per week. A second bar/line graph 520 shows storage efficiencies related to transfer time. Bar graphs are distributed along the x-axis, and relate to full backup time, incremental backup time, and offsite copy time. A third bar graph 530 shows storage efficiencies for a two year data footprint.

Value data for risk reduction includes a list of risk elements 540 that a user is exposed to. Value data also includes a data and information risk exposure score for the alternate system (score=4.82) and the integrated system (score=1.73). A table additionally compares the alternative/existing system and the integrated system as percent backup reliability, percent restore reliability, number of hours unplanned downtime, and number of RPO minutes. A graph and line chart 560 shows protection efficiencies between the alternative system and the integrated system for Microsoft Exchange restore time, Oracle database restore time, SQL restore time, and virtual machine (VM) restore time. Value data associated with unlocking data value includes a table 570 containing data related to savings, gains, and value of having data available to the user. A bar chart 580 shows data value efficiencies between an integrated system and an alternative system with reference to file recovery and message recovery. After the system generates the value dashboard, the process 300 returns. The system may take elements of the dashboard and insert them into a slide presentation to be presented or displayed to a user or prospect.

One way for the system to portray the value of using an integrated data management and protection system is through value stories. A value story may be produced by an interactive presentation application. The value story is comprised of multiple displays, which provide an interface to convey value to and receive input from a user. Each display of a value story may relate to a particular aspect of a user's data management and protection needs. For example, a first display may request information associated with a user's IT department and a second display may request information associated with the user's management.

FIGS. 6A and 6B show interfaces for presenting a simple value story. FIG. 6A shows a GUI for an interactive presentation application that includes various, simplified data entry fields and sliders for a user to manipulate. After a user submits information via the sliders/entry fields, the system generates a dashboard for conveying values. The system may implement a process analogous to the process described with respect to FIG. 3 to present data, receive user input, and identify value associated with an integrated data management and protection system. FIG. 6B shows a dashboard for portraying value associated with an integrated data management and protection system based on data input via the GUI of FIG. 6A. In this example, a bar chart shows the great reduction in certain data storage categories by adopting the integrated data storage system over that of a standard system without any data reduction (e.g. large reduction in tape storage and cloud copies). A value story can be used by a person to identify value for a user early on in a sales cycle, before the person has learned details about a user's data management and protection needs.

FIG. 7 shows an illustrative graphical user interface or display showing a value story for conveying value of a user implementing a data management and protection system such as for cloud management. Overall, the system can generate a specific value comparison, including cost. Of course, many other displays are possible for other aspects of data storage and management, and described herein.

As discussed throughout, the system 200 identifies value with respect to at least three value categories, where these categories are multifaceted. First, simplification and efficiency include reductions in: administrative overhead; infrastructure cost and complexity; planned full-time employee hires; and total storage footprint. An integrated system, e.g. reduces weekly administrative hours across multiple categories, improves backup and offsite copy time, reduces the need to hire additional full-time employees, and reduces total terabytes backed up, carried over network, and stored on secondary tiers. Combined, these benefits reduce complexity in the data storage environment and improve efficiencies.

Second, risk reduction includes: operational improvements; reductions in application recovery time; and reductions in subjective measure of exposure to compliance failures, litigation issues or data loss. An integrated system, e.g. increases backup reliability, reduces average application recovery point objectives, and delivers significant reductions in application and database recovery time. Additional factors such as reduced complexity in the IT environment and improved data access also contribute to risk reduction. Combined, these benefits significantly improve data protection and recovery operations and reduce organizational exposure to downtime as well as revenue and data loss.

Third, unlocking data value includes: reductions in object recovery time, indexing and housing of all managed data, storing data in single virtual repository, access for IT and end-users to the data, and making IT more strategic to the business. The integrated system, e.g. reduces file recovery time, reduces message recovery time, provides faster time to value over previous systems, reduces litigation discovery costs, and drives employee productivity gains. These benefits can combine to make an integrated data management system more strategically important to an organization relative to competitive data management systems. The benefit of the present system is that it calculates, organizes, and summarizes these potential benefits in a unique and compelling way for any user contemplating the purchase of an integrated data management system.

The DIRE Index score, noted above, may include five elements or categories of risk: 1. Downtime, 2. IT Complexity, 3. Data Protection Efficiency, 4. Recovery Efficiency, and 5. Operational Exposure, which may be defined as follows:

Downtime: average number of hours of unplanned downtime that impact an organization annually;

IT Complexity: number of hardware, software, snapshot, replication and scripting vendors and/or solutions the information management system must support;

Protection Efficiency: reliability and efficiency of an organization's data protection operations;

Recovery Efficiency: speed, efficiency, reliability and scope of an organization's recovery capabilities; and

Operational Exposure: amount of protection, encryption and reporting coverage an organization can provide across its data; how exposed the organization is to compliance failures, legal issues and data loss; also included in this category is an organization's “subjective level of risk”—while not weighted highly algorithmically, it is important to consider each organization's subjective understanding of its data exposure when generating a comprehensive Index score.

IT Complexity category, in smaller environments, can be measured by a number of disk arrays, software products, and specific scripts within a current or proposed/competitive environment. The present system can compare this to an anticipated number of arrays, software solutions and scripts that would be required in the integrated system. In larger environments, multi-petabyte environments, for example, IT Complexity can be measured in the aggregate—the number of hardware and software vendors (as opposed to arrays), or the number of application or database environments (vs. individual databases) that require scripting support. In either case, the risk principle remains the same: the greater the complexity, the greater the risk. Complexity makes it more difficult to bring multiple systems back online after an outage; more time consuming to perform recovery; and more difficult to protect and secure an environment tied together with multiple scripts.

Advantageously, the integrated information management system described in detail above often eliminates multiple, sometimes dozens of software solutions and hardware silos by virtualizing storage for backup, archive, snapshot, compliance and discovery data under a single index. A single index in the integrated system makes it easier to restore multiple systems after an outage; significantly reduces recovery time; makes it easier to secure and environment; eliminate scripts; and simplifies IT operations across the board. Simplifying IT environments and reducing IT complexity reduces risk. The system therefore weights IT Complexity highly in the Index score.

The Index score represents relative risk for any IT environment. As noted herein, the Index score is based on an accumulated score of individual metrics, where each metric is a measurable attribute of the installation's environment that represents an element of risk to the data such as the amount of time it takes to perform a backup or the number of recovery points per day.

Examples of alternative or additional user interfaces are shown with respect to FIGS. 8A through 9E. FIG. 8A and 9E sure comparison between an existing or “point product” and an integrated system (“Commvault”), with respect to virtualization. FIGS. 8A through 8E show similar user interfaces, but for loaded recovery costs, recovery capabilities and legal discovery savings as calculated and displayed by the present system.

FIG. 9A shows a user interface that conveys to a user five elements used by the present system to compute the DIRE Index score. FIGS. 9B and 9C show user interfaces that let a user to input data into the system, as described above. FIGS. 9D and 9E show sample output provided by the present system to show a computed Index score for a user's current system versus an integrated system, together with corresponding data used to generate the score.

Note, the system may employ two types of data input to the system for generating the Index score and other values. The first type of data is data previously gathered via survey related to performance of existing information management systems, which may be statistically validated, e.g. by third party consultant. This data is then used as empirically derived data for input to the elements or categories of risk noted above. This prior user data provides baseline values for different areas of impact and different metrics of value, providing a credible foundation when presenting value calculations back to users. The second type of data is data supplied by the current user of the system using the user interfaces discussed above. Users can change these values freely, but the prior user data provides the credible baseline—empirical data to provide more accurate, automatic data calculations

In other words, there is a distinction between data supplied by the user of the various Value Tools (the second type of data), and data built into the Value Tools based on previous surveys and prior usage (the first type of data). For example, FIGS. 8D, 9C and 9E all incorporate baseline Recovery Time Reductions that may be obtained from surveys or from other empirically derived ways. The data from our user surveys is incorporated into the calculations noted above, so that the system can provide default values for, e.g., average Recovery Time Reductions as reported by prior users. The user of the Value Calculator can adjust the different factors/categories—but often the baseline data is supplied by the earlier user survey data.

Terminology

Conditional language, such as, among others, “can,” “could,” “might,” or “may,” unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain embodiments include, while other embodiments do not include, certain features, elements and/or steps. Thus, such conditional language is not generally intended to imply that features, elements and/or steps are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without user input or prompting, whether these features, elements and/or steps are included or are to be performed in any particular embodiment.

Unless the context clearly requires otherwise, throughout the description and the claims, the words “comprise,” “comprising,” and the like are to be construed in an inclusive sense, as opposed to an exclusive or exhaustive sense; that is to say, in the sense of “including, but not limited to.” As used herein, the terms “connected,” “coupled,” or any variant thereof means any connection or coupling, either direct or indirect, between two or more elements; the coupling or connection between the elements can be physical, logical, or a combination thereof. Additionally, the words “herein,” “above,” “below,” and words of similar import, when used in this application, refer to this application as a whole and not to any particular portions of this application. Where the context permits, words in the above Detailed Description using the singular or plural number may also include the plural or singular number respectively. The word “or” in reference to a list of two or more items, covers all of the following interpretations of the word: any one of the items in the list, all of the items in the list, and any combination of the items in the list. Likewise the term “and/or” in reference to a list of two or more items, covers all of the following interpretations of the word: any one of the items in the list, all of the items in the list, and any combination of the items in the list.

Depending on the embodiment, certain operations, acts, events, or functions of any of the algorithms described herein can be performed in a different sequence, can be added, merged, or left out altogether (e.g., not all are necessary for the practice of the algorithms). Moreover, in certain embodiments, operations, acts, functions, or events can be performed concurrently, e.g., through multi-threaded processing, interrupt processing, or multiple processors or processor cores or on other parallel architectures, rather than sequentially.

Systems and modules described herein may comprise software, firmware, hardware, or any combination(s) of software, firmware, or hardware suitable for the purposes described herein. Software and other modules may reside and execute on servers, workstations, personal computers, computerized tablets, PDAs, and other computing devices suitable for the purposes described herein. Software and other modules may be accessible via local memory, via a network, via a browser, or via other means suitable for the purposes described herein. Data structures described herein may comprise computer files, variables, programming arrays, programming structures, or any electronic information storage schemes or methods, or any combinations thereof, suitable for the purposes described herein. User interface elements described herein may comprise elements from graphical user interfaces, interactive voice response, command line interfaces, and other suitable interfaces.

Further, the processing of the various components of the illustrated systems can be distributed across multiple machines, networks, and other computing resources. In addition, two or more components of a system can be combined into fewer components. Various components of the illustrated systems can be implemented in one or more virtual machines, rather than in dedicated computer hardware systems and/or computing devices. Likewise, the data repositories shown can represent physical and/or logical data storage, including, for example, storage area networks or other distributed storage systems. Moreover, in some embodiments the connections between the components shown represent possible paths of data flow, rather than actual connections between hardware. While some examples of possible connections are shown, any of the subset of the components shown can communicate with any other subset of components in various implementations.

Embodiments are also described above with reference to flow chart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products. Each block of the flow chart illustrations and/or block diagrams, and combinations of blocks in the flow chart illustrations and/or block diagrams, may be implemented by computer program instructions. Such instructions may be provided to a processor of a general purpose computer, special purpose computer, specially-equipped computer (e.g., comprising a high-performance database server, a graphics subsystem, etc.) or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor(s) of the computer or other programmable data processing apparatus, create means for implementing the acts specified in the flow chart and/or block diagram block or blocks.

These computer program instructions may also be stored in a non-transitory computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the acts specified in the flow chart and/or block diagram block or blocks. The computer program instructions may also be loaded onto a computing device or other programmable data processing apparatus to cause a series of operations to be performed on the computing device or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the acts specified in the flow chart and/or block diagram block or blocks.

Any patents and applications and other references noted above, including any that may be listed in accompanying filing papers, are incorporated herein by reference. Aspects of the invention can be modified, if necessary, to employ the systems, functions, and concepts of the various references described above to provide yet further implementations of the invention.

These and other changes can be made to the invention in light of the above Detailed Description. While the above description describes certain examples of the invention, and describes the best mode contemplated, no matter how detailed the above appears in text, the invention can be practiced in many ways. Details of the system may vary considerably in its specific implementation, while still being encompassed by the invention disclosed herein. As noted above, particular terminology used when describing certain features or aspects of the invention should not be taken to imply that the terminology is being redefined herein to be restricted to any specific characteristics, features, or aspects of the invention with which that terminology is associated. In general, the terms used in the following claims should not be construed to limit the invention to the specific examples disclosed in the specification, unless the above Detailed Description section explicitly defines such terms. Accordingly, the actual scope of the invention encompasses not only the disclosed examples, but also all equivalent ways of practicing or implementing the invention under the claims.

To reduce the number of claims, certain aspects of the invention are presented below in certain claim forms, but the applicant contemplates the various aspects of the invention in any number of claim forms. For example, while only one aspect of the invention is recited as a means-plus-function claim under 35 U.S.C sec. 112(f) (AIA), other aspects may likewise be embodied as a means-plus-function claim, or in other forms, such as being embodied in a computer-readable medium. Any claims intended to be treated under 35 U.S.C. §112(f) will begin with the words “means for”, but use of the term “for” in any other context is not intended to invoke treatment under 35 U.S.C. §112(f). Accordingly, the applicant reserves the right to pursue additional claims after filing this application, in either this application or in a continuing application. 

What is claimed is:
 1. A tangible computer-readable storage medium, excluding transitory signals, and which contains instructions for performing a method of identifying and portraying data associated with implementing an integrated data management and protection system, the method comprising: maintaining value functions for quantifying value associated with implementing an integrated data management and protection system; wherein the integrated data management and protection system performs archiving, backup, and at least one other data management function; receiving user input requesting information describing value associated with implementing the integrated data management and protection system, wherein the value associated with implementing the integrated data management and protection system relates to cost reduction, risks, and obtaining value from data; generating an interface that displays a request for a user to submit, via the interface, information associated with data management and protection, wherein the interface includes data entry fields for receiving information associated with data management and protection, and wherein the information associated with data management and protection includes information related to: complexity of an existing data management and protection system, data protection reliability, data recovery time, and operational oversight for the existing data management and protection system; receiving user-submitted information via the data entry fields of the interface; weighting at least some of the received user-submitted information; identifying value functions for quantifying value associated with implementing the integrated data management and protection system; applying the value functions to the received information, wherein the value functions result in value data for the integrated data management and protection system when applied to the received user-submitted information, and wherein the applying includes generating a single, combined index score that aggregates the value data obtained by applying the value functions to the weighted, user-submitted information; and, generating a value dashboard that displays the value data for the integrated data management and protection system, wherein the value data is indicative of value associated with implementing the integrated data management and protection system versus use of the existing data management and protection system, and wherein the dashboard includes the combined index score.
 2. The tangible computer-readable storage medium of claim 1, further comprising: identifying alternative value functions for quantifying value associated with implementing an alternative data management and protection system; and applying the identified alternative value functions to the received user-submitted information, wherein the identified alternative value functions result in alternative value data for the alternative data management and protection system when applied to the received user-submitted information, and wherein the value dashboard displays the alternative value data relative to the value data indicative of value associated with implementing the integrated data management and protection system.
 3. The tangible computer-readable storage medium of claim 1, wherein generating a value dashboard that displays the value data includes displaying the value data with reference to three categories of value: simplification, risk reduction, and data value.
 4. The tangible computer-readable storage medium of claim 1, wherein the integrated data management and protection system performs at least the following functions: archiving, backup, snapshot management, reporting, secure data access, eDiscovery and data analytics.
 5. The tangible computer-readable storage medium of claim 1, wherein the value dashboard displays information describing a value story of an integrated data management and protection system.
 6. The tangible computer-readable storage medium of claim 1, wherein a value function of the value functions applied to the received information is associated with risk reduction, and wherein the value function results in a single score indicating relative risk associated with the integrated data management and protection system.
 7. A computer-implemented method for identifying and portraying information associated with implementing an integrated data management system, the method comprising: maintaining value functions for quantifying value associated with implementing an integrated data management system; wherein the integrated data management system performs archiving, backup, and at least one other data management function; generating an interface to display a request to submit, via the interface, information associated with an existing data management system, wherein the interface includes data entry fields for receiving information associated with the existing data management system, and wherein the information associated with the existing data management system includes information related to: complexity of the existing data management and protection system, data protection reliability, data recovery time, and operational oversight for the existing data management and protection system; receiving information submitted via the data entry fields of the interface; applying weights to the received information; applying value functions to the received information, wherein the value functions calculate values related to performance of the existing data management system based on the received information, and calculate values related to performance of the integrated data management system based on the received information, wherein the values related to performance of the existing data management system relate to cost reduction, risks and obtaining value from data, and wherein applying value functions includes generating an index score that represents an aggregation of the calculated values related to the existing data management system based on the received information; and, generating a dashboard that displays the calculated values related to performance of the integrated data management system and the existing data management system, wherein the calculated values include a comparison between performance of the integrated data management and the existing data management system, and wherein the dashboard is configured to display the index score and a relative risk associated with the index score.
 8. The method of claim 7, further comprising: identifying alternative value functions for quantifying value associated with the user implementing an alternative data management system; and applying the identified alternative value functions to the received information, wherein the alternative value functions result in alternative value data for the alternative data management system when applied to the received information, and wherein the value dashboard displays the alternative value data relative to the value data indicative of value associated with implementing the integrated data management system.
 9. The method of claim 7, wherein generating a value dashboard that displays the value data includes displaying the value data with reference to three categories of value: simplification, risk reduction, and data value.
 10. The method of claim 7, wherein the integrated data management system performs at least the following functions: archiving, backup, snapshot management, reporting, secure data access, eDiscovery and data analytics.
 11. The method of claim 7, wherein the value dashboard displays data describing a value story of the integrated data management system.
 12. The method of claim 7, wherein a value function of the value functions applied to the received information is associated with risk reduction, and wherein the value function results in a single score indicating relative risk associated with the integrated data management and protection system.
 13. A non-transitory computer-readable storage medium containing instructions for performing a method of identifying and portraying to a user value associated with implementing an integrated data management and protection system, the method comprising: receiving from a user a request for information describing value associated with a user implementing the integrated data management and protection system, generating an interface that displays a request for the user to submit, via the interface, information associated with data management and protection for the user, wherein the interface includes data entry fields for receiving, from the user, information associated with data management and protection for the user, and wherein the information associated with the data management and protection for the user includes information related to— complexity of an existing data management and protection system, data protection reliability, data recovery time, and operational oversight for the existing data management and protection system; receiving information submitted by the user via the data entry fields of the interface; quantifying value associated with an integrated data management and protection system based at least in part on the received information, wherein the value is quantified in relation to at least three value categories to generate quantified values, wherein the value categories include simplification, risk reduction, and data value; and generating a value dashboard that displays the quantified values associated with the integrated data management and protection system, wherein the dashboard displays a single index score that represents an aggregation of the quantified values related to the received information associated with the data management and protection for the user.
 14. The non-transitory computer-readable storage medium of claim 13, further comprising: quantifying value associated with an alternative data management and protection system based at least in part on the received information; and wherein the value dashboard displays the alternative value data relative to the value data indicative of value associated with the user implementing the integrated data management and protection system.
 15. The non-transitory computer-readable storage medium of claim 13, wherein the integrated data management and protection system performs at least the following functions: archiving, backup, snapshot management, reporting, secure data access, eDiscovery and data analytics.
 16. The non-transitory computer-readable storage medium of claim 13, wherein the value dashboard displays vignettes describing a value story of an integrated data management and protection system for the user. 